diff --git "a/GEMMA_9B_B10_MMLU_H.ipynb" "b/GEMMA_9B_B10_MMLU_H.ipynb"
new file mode 100644--- /dev/null
+++ "b/GEMMA_9B_B10_MMLU_H.ipynb"
@@ -0,0 +1,8922 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "id": "0c24ca36-1782-4ce8-8094-6f6528dada19",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 17,
+          "referenced_widgets": [
+            "e45f01941b984da59c8215e5d0fdbc33",
+            "c1af9f9962f14181b56af5c6340f41ad",
+            "3381a25afa1a4ac4b65c531feb5f9407",
+            "ade207c5bb44485dae09a5a3fc414bfb",
+            "96f8ae744112403aa1c2415772cf5faf",
+            "1f51d19ea1d84b0aa8d7635e873eb8fb",
+            "e8026b1bf4f948f7a67ab753bdc16565",
+            "9a798dd18fca4140ae6d03085ae83629",
+            "5f2179c1a6314af88adca5856ed397f5",
+            "907d0f51a73748e9a7cda50e7bb58c35",
+            "78736d1cec3f4bcc9d2a59672ee4bb40",
+            "84e2f6d79bb04e388fd6053fc0207efd",
+            "7fa40ed7a38b4924902dfe6c1ff952f8",
+            "904403c8a1334588bee0c629a8518a5d",
+            "da9cc5f3770547759a5366c3410bf23b",
+            "8bebf7a327364c05b04aae6d5def58ff",
+            "91105ed7122b4dfd9619f181ba8a838a",
+            "1511905fb6244d319a5d571c6f0d718d",
+            "a1d5b347418e473793ef7496bc9a6e21",
+            "45463d2f2148403c9ce4a8d743ba2925"
+          ]
+        },
+        "id": "0c24ca36-1782-4ce8-8094-6f6528dada19",
+        "outputId": "ab783659-69fd-42c5-c28a-bc05875b228d"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "e45f01941b984da59c8215e5d0fdbc33"
+            }
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "from huggingface_hub import notebook_login\n",
+        "notebook_login()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install unsloth\n",
+        "!pip install --force-reinstall --no-cache-dir --no-deps git+https://github.com/unslothai/unsloth.git"
+      ],
+      "metadata": {
+        "id": "REqA0fPKcTST",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "outputId": "f73bff1a-2292-4790-860f-6de8e80ac2b3"
+      },
+      "id": "REqA0fPKcTST",
+      "execution_count": 2,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Collecting unsloth\n",
+            "  Downloading unsloth-2025.1.6-py3-none-any.whl.metadata (53 kB)\n",
+            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/53.7 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m53.7/53.7 kB\u001b[0m \u001b[31m2.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hCollecting unsloth_zoo>=2025.1.4 (from unsloth)\n",
+            "  Downloading unsloth_zoo-2025.1.5-py3-none-any.whl.metadata (16 kB)\n",
+            "Requirement already satisfied: torch>=2.4.0 in /usr/local/lib/python3.11/dist-packages (from unsloth) (2.5.1+cu121)\n",
+            "Collecting xformers>=0.0.27.post2 (from unsloth)\n",
+            "  Downloading xformers-0.0.29.post1-cp311-cp311-manylinux_2_28_x86_64.whl.metadata (1.0 kB)\n",
+            "Collecting bitsandbytes (from unsloth)\n",
+            "  Downloading bitsandbytes-0.45.1-py3-none-manylinux_2_24_x86_64.whl.metadata (5.8 kB)\n",
+            "Requirement already satisfied: triton>=3.0.0 in /usr/local/lib/python3.11/dist-packages (from unsloth) (3.1.0)\n",
+            "Requirement already satisfied: packaging in /usr/local/lib/python3.11/dist-packages (from unsloth) (24.2)\n",
+            "Collecting tyro (from unsloth)\n",
+            "  Downloading tyro-0.9.13-py3-none-any.whl.metadata (9.4 kB)\n",
+            "Requirement already satisfied: transformers!=4.47.0,>=4.46.1 in /usr/local/lib/python3.11/dist-packages (from unsloth) (4.47.1)\n",
+            "Collecting datasets>=2.16.0 (from unsloth)\n",
+            "  Downloading datasets-3.2.0-py3-none-any.whl.metadata (20 kB)\n",
+            "Requirement already satisfied: sentencepiece>=0.2.0 in /usr/local/lib/python3.11/dist-packages (from unsloth) (0.2.0)\n",
+            "Requirement already satisfied: tqdm in /usr/local/lib/python3.11/dist-packages (from unsloth) (4.67.1)\n",
+            "Requirement already satisfied: psutil in /usr/local/lib/python3.11/dist-packages (from unsloth) (5.9.5)\n",
+            "Requirement already satisfied: wheel>=0.42.0 in /usr/local/lib/python3.11/dist-packages (from unsloth) (0.45.1)\n",
+            "Requirement already satisfied: numpy in /usr/local/lib/python3.11/dist-packages (from unsloth) (1.26.4)\n",
+            "Requirement already satisfied: accelerate>=0.34.1 in /usr/local/lib/python3.11/dist-packages (from unsloth) (1.2.1)\n",
+            "Collecting trl!=0.9.0,!=0.9.1,!=0.9.2,!=0.9.3,>=0.7.9 (from unsloth)\n",
+            "  Downloading trl-0.13.0-py3-none-any.whl.metadata (11 kB)\n",
+            "Requirement already satisfied: peft!=0.11.0,>=0.7.1 in /usr/local/lib/python3.11/dist-packages (from unsloth) (0.14.0)\n",
+            "Collecting protobuf<4.0.0 (from unsloth)\n",
+            "  Downloading protobuf-3.20.3-py2.py3-none-any.whl.metadata (720 bytes)\n",
+            "Requirement already satisfied: huggingface_hub in /usr/local/lib/python3.11/dist-packages (from unsloth) (0.27.1)\n",
+            "Collecting hf_transfer (from unsloth)\n",
+            "  Downloading hf_transfer-0.1.9-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (1.7 kB)\n",
+            "Requirement already satisfied: pyyaml in /usr/local/lib/python3.11/dist-packages (from accelerate>=0.34.1->unsloth) (6.0.2)\n",
+            "Requirement already satisfied: safetensors>=0.4.3 in /usr/local/lib/python3.11/dist-packages (from accelerate>=0.34.1->unsloth) (0.5.2)\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from datasets>=2.16.0->unsloth) (3.17.0)\n",
+            "Requirement already satisfied: pyarrow>=15.0.0 in /usr/local/lib/python3.11/dist-packages (from datasets>=2.16.0->unsloth) (17.0.0)\n",
+            "Collecting dill<0.3.9,>=0.3.0 (from datasets>=2.16.0->unsloth)\n",
+            "  Downloading dill-0.3.8-py3-none-any.whl.metadata (10 kB)\n",
+            "Requirement already satisfied: pandas in /usr/local/lib/python3.11/dist-packages (from datasets>=2.16.0->unsloth) (2.2.2)\n",
+            "Requirement already satisfied: requests>=2.32.2 in /usr/local/lib/python3.11/dist-packages (from datasets>=2.16.0->unsloth) (2.32.3)\n",
+            "Collecting xxhash (from datasets>=2.16.0->unsloth)\n",
+            "  Downloading xxhash-3.5.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (12 kB)\n",
+            "Collecting multiprocess<0.70.17 (from datasets>=2.16.0->unsloth)\n",
+            "  Downloading multiprocess-0.70.16-py311-none-any.whl.metadata (7.2 kB)\n",
+            "Collecting fsspec<=2024.9.0,>=2023.1.0 (from fsspec[http]<=2024.9.0,>=2023.1.0->datasets>=2.16.0->unsloth)\n",
+            "  Downloading fsspec-2024.9.0-py3-none-any.whl.metadata (11 kB)\n",
+            "Requirement already satisfied: aiohttp in /usr/local/lib/python3.11/dist-packages (from datasets>=2.16.0->unsloth) (3.11.11)\n",
+            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub->unsloth) (4.12.2)\n",
+            "Requirement already satisfied: networkx in /usr/local/lib/python3.11/dist-packages (from torch>=2.4.0->unsloth) (3.4.2)\n",
+            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.11/dist-packages (from torch>=2.4.0->unsloth) (3.1.5)\n",
+            "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.1.105 in /usr/local/lib/python3.11/dist-packages (from torch>=2.4.0->unsloth) (12.1.105)\n",
+            "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /usr/local/lib/python3.11/dist-packages (from torch>=2.4.0->unsloth) (12.1.105)\n",
+            "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /usr/local/lib/python3.11/dist-packages (from torch>=2.4.0->unsloth) (12.1.105)\n",
+            "Requirement already satisfied: nvidia-cudnn-cu12==9.1.0.70 in /usr/local/lib/python3.11/dist-packages (from torch>=2.4.0->unsloth) (9.1.0.70)\n",
+            "Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /usr/local/lib/python3.11/dist-packages (from torch>=2.4.0->unsloth) (12.1.3.1)\n",
+            "Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /usr/local/lib/python3.11/dist-packages (from torch>=2.4.0->unsloth) (11.0.2.54)\n",
+            "Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /usr/local/lib/python3.11/dist-packages (from torch>=2.4.0->unsloth) (10.3.2.106)\n",
+            "Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /usr/local/lib/python3.11/dist-packages (from torch>=2.4.0->unsloth) (11.4.5.107)\n",
+            "Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /usr/local/lib/python3.11/dist-packages (from torch>=2.4.0->unsloth) (12.1.0.106)\n",
+            "Requirement already satisfied: nvidia-nccl-cu12==2.21.5 in /usr/local/lib/python3.11/dist-packages (from torch>=2.4.0->unsloth) (2.21.5)\n",
+            "Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /usr/local/lib/python3.11/dist-packages (from torch>=2.4.0->unsloth) (12.1.105)\n",
+            "Requirement already satisfied: sympy==1.13.1 in /usr/local/lib/python3.11/dist-packages (from torch>=2.4.0->unsloth) (1.13.1)\n",
+            "Requirement already satisfied: nvidia-nvjitlink-cu12 in /usr/local/lib/python3.11/dist-packages (from nvidia-cusolver-cu12==11.4.5.107->torch>=2.4.0->unsloth) (12.6.85)\n",
+            "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from sympy==1.13.1->torch>=2.4.0->unsloth) (1.3.0)\n",
+            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.11/dist-packages (from transformers!=4.47.0,>=4.46.1->unsloth) (2024.11.6)\n",
+            "Requirement already satisfied: tokenizers<0.22,>=0.21 in /usr/local/lib/python3.11/dist-packages (from transformers!=4.47.0,>=4.46.1->unsloth) (0.21.0)\n",
+            "Requirement already satisfied: rich in /usr/local/lib/python3.11/dist-packages (from trl!=0.9.0,!=0.9.1,!=0.9.2,!=0.9.3,>=0.7.9->unsloth) (13.9.4)\n",
+            "Collecting cut_cross_entropy (from unsloth_zoo>=2025.1.4->unsloth)\n",
+            "  Downloading cut_cross_entropy-25.1.1-py3-none-any.whl.metadata (9.3 kB)\n",
+            "Requirement already satisfied: pillow in /usr/local/lib/python3.11/dist-packages (from unsloth_zoo>=2025.1.4->unsloth) (11.1.0)\n",
+            "Requirement already satisfied: docstring-parser>=0.15 in /usr/local/lib/python3.11/dist-packages (from tyro->unsloth) (0.16)\n",
+            "Collecting shtab>=1.5.6 (from tyro->unsloth)\n",
+            "  Downloading shtab-1.7.1-py3-none-any.whl.metadata (7.3 kB)\n",
+            "Requirement already satisfied: typeguard>=4.0.0 in /usr/local/lib/python3.11/dist-packages (from tyro->unsloth) (4.4.1)\n",
+            "Requirement already satisfied: aiohappyeyeballs>=2.3.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets>=2.16.0->unsloth) (2.4.4)\n",
+            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets>=2.16.0->unsloth) (1.3.2)\n",
+            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets>=2.16.0->unsloth) (24.3.0)\n",
+            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets>=2.16.0->unsloth) (1.5.0)\n",
+            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets>=2.16.0->unsloth) (6.1.0)\n",
+            "Requirement already satisfied: propcache>=0.2.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets>=2.16.0->unsloth) (0.2.1)\n",
+            "Requirement already satisfied: yarl<2.0,>=1.17.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets>=2.16.0->unsloth) (1.18.3)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets>=2.16.0->unsloth) (3.4.1)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets>=2.16.0->unsloth) (3.10)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets>=2.16.0->unsloth) (2.3.0)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets>=2.16.0->unsloth) (2024.12.14)\n",
+            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.11/dist-packages (from rich->trl!=0.9.0,!=0.9.1,!=0.9.2,!=0.9.3,>=0.7.9->unsloth) (3.0.0)\n",
+            "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.11/dist-packages (from rich->trl!=0.9.0,!=0.9.1,!=0.9.2,!=0.9.3,>=0.7.9->unsloth) (2.18.0)\n",
+            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.11/dist-packages (from jinja2->torch>=2.4.0->unsloth) (3.0.2)\n",
+            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.11/dist-packages (from pandas->datasets>=2.16.0->unsloth) (2.8.2)\n",
+            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.11/dist-packages (from pandas->datasets>=2.16.0->unsloth) (2024.2)\n",
+            "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.11/dist-packages (from pandas->datasets>=2.16.0->unsloth) (2025.1)\n",
+            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.11/dist-packages (from markdown-it-py>=2.2.0->rich->trl!=0.9.0,!=0.9.1,!=0.9.2,!=0.9.3,>=0.7.9->unsloth) (0.1.2)\n",
+            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.11/dist-packages (from python-dateutil>=2.8.2->pandas->datasets>=2.16.0->unsloth) (1.17.0)\n",
+            "Downloading unsloth-2025.1.6-py3-none-any.whl (175 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m175.5/175.5 kB\u001b[0m \u001b[31m6.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading datasets-3.2.0-py3-none-any.whl (480 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m480.6/480.6 kB\u001b[0m \u001b[31m20.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading protobuf-3.20.3-py2.py3-none-any.whl (162 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m162.1/162.1 kB\u001b[0m \u001b[31m17.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading trl-0.13.0-py3-none-any.whl (293 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m293.4/293.4 kB\u001b[0m \u001b[31m21.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading unsloth_zoo-2025.1.5-py3-none-any.whl (80 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m80.2/80.2 kB\u001b[0m \u001b[31m5.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading xformers-0.0.29.post1-cp311-cp311-manylinux_2_28_x86_64.whl (15.3 MB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m15.3/15.3 MB\u001b[0m \u001b[31m105.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading bitsandbytes-0.45.1-py3-none-manylinux_2_24_x86_64.whl (69.7 MB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m69.7/69.7 MB\u001b[0m \u001b[31m29.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading hf_transfer-0.1.9-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.6 MB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.6/3.6 MB\u001b[0m \u001b[31m80.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading tyro-0.9.13-py3-none-any.whl (115 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m115.7/115.7 kB\u001b[0m \u001b[31m11.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading dill-0.3.8-py3-none-any.whl (116 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m116.3/116.3 kB\u001b[0m \u001b[31m10.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading fsspec-2024.9.0-py3-none-any.whl (179 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m179.3/179.3 kB\u001b[0m \u001b[31m15.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading multiprocess-0.70.16-py311-none-any.whl (143 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m143.5/143.5 kB\u001b[0m \u001b[31m13.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading shtab-1.7.1-py3-none-any.whl (14 kB)\n",
+            "Downloading cut_cross_entropy-25.1.1-py3-none-any.whl (22 kB)\n",
+            "Downloading xxhash-3.5.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (194 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.8/194.8 kB\u001b[0m \u001b[31m17.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hInstalling collected packages: xxhash, shtab, protobuf, hf_transfer, fsspec, dill, multiprocess, tyro, xformers, datasets, cut_cross_entropy, bitsandbytes, trl, unsloth_zoo, unsloth\n",
+            "  Attempting uninstall: protobuf\n",
+            "    Found existing installation: protobuf 4.25.5\n",
+            "    Uninstalling protobuf-4.25.5:\n",
+            "      Successfully uninstalled protobuf-4.25.5\n",
+            "  Attempting uninstall: fsspec\n",
+            "    Found existing installation: fsspec 2024.10.0\n",
+            "    Uninstalling fsspec-2024.10.0:\n",
+            "      Successfully uninstalled fsspec-2024.10.0\n",
+            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+            "gcsfs 2024.10.0 requires fsspec==2024.10.0, but you have fsspec 2024.9.0 which is incompatible.\n",
+            "tensorflow-metadata 1.16.1 requires protobuf<6.0.0dev,>=4.25.2; python_version >= \"3.11\", but you have protobuf 3.20.3 which is incompatible.\n",
+            "grpcio-status 1.62.3 requires protobuf>=4.21.6, but you have protobuf 3.20.3 which is incompatible.\u001b[0m\u001b[31m\n",
+            "\u001b[0mSuccessfully installed bitsandbytes-0.45.1 cut_cross_entropy-25.1.1 datasets-3.2.0 dill-0.3.8 fsspec-2024.9.0 hf_transfer-0.1.9 multiprocess-0.70.16 protobuf-3.20.3 shtab-1.7.1 trl-0.13.0 tyro-0.9.13 unsloth-2025.1.6 unsloth_zoo-2025.1.5 xformers-0.0.29.post1 xxhash-3.5.0\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "application/vnd.colab-display-data+json": {
+              "pip_warning": {
+                "packages": [
+                  "google"
+                ]
+              },
+              "id": "1da8cdc4402448ccbc0a22cab4c6df88"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Collecting git+https://github.com/unslothai/unsloth.git\n",
+            "  Cloning https://github.com/unslothai/unsloth.git to /tmp/pip-req-build-v8x0l7jh\n",
+            "  Running command git clone --filter=blob:none --quiet https://github.com/unslothai/unsloth.git /tmp/pip-req-build-v8x0l7jh\n",
+            "  Resolved https://github.com/unslothai/unsloth.git to commit bdf0cd6033595be4e7ed23d0d002bb176d343152\n",
+            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
+            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
+            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
+            "Building wheels for collected packages: unsloth\n",
+            "  Building wheel for unsloth (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for unsloth: filename=unsloth-2025.1.7-py3-none-any.whl size=174896 sha256=c34c896c097ba0b49aab5a8aa2c98ffcaf25f978810edb1fdd89924d20e11950\n",
+            "  Stored in directory: /tmp/pip-ephem-wheel-cache-7e7r7xi9/wheels/d1/17/05/850ab10c33284a4763b0595cd8ea9d01fce6e221cac24b3c01\n",
+            "Successfully built unsloth\n",
+            "Installing collected packages: unsloth\n",
+            "  Attempting uninstall: unsloth\n",
+            "    Found existing installation: unsloth 2025.1.6\n",
+            "    Uninstalling unsloth-2025.1.6:\n",
+            "      Successfully uninstalled unsloth-2025.1.6\n",
+            "Successfully installed unsloth-2025.1.7\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 55,
+      "id": "fbc9900d-28d2-4bda-9848-b572fbe778d2",
+      "metadata": {
+        "id": "fbc9900d-28d2-4bda-9848-b572fbe778d2",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 575,
+          "referenced_widgets": [
+            "174f06d96a414316a2312c09f34f712e",
+            "c08ac93850bb4e0da4e615d5a2c54ea0",
+            "64bfcdc6238144659413b70f23ecd225",
+            "450ee7e1025a4a72b6d0829c3a2b3f63",
+            "cc936c061dc24a378944f0789480f71e",
+            "af075b28873e440baeca0d3bd1326568",
+            "d7e0bbd0c277432d9f401168e157ad8d",
+            "20577fc6bce047979e0a00436ccbd4b5",
+            "0d1200471c634cb88c35131fb6bb8138",
+            "f6710c96595c40d7868f341f2c12fc83",
+            "bd3c8bd7b391470e8a4f73f9ffa7b3a4",
+            "524de86a695f480eb439a8fd86b21864",
+            "6b3f49b308184d2c8ebbf9e147412404",
+            "53f83486f9d745b0a624b05d07ba3d8d",
+            "7311811bb4bb46908a296fca1ede115b",
+            "204838c48ca7472e9ebf7dbf33634eb0",
+            "4325dadbd09b4dc29da3c0a85bc5fd7f",
+            "05ca7a0b6350455d89a717ddc2e63a85",
+            "c090b7a2afac4fcb984b01087222a3f9",
+            "3833525d061a4a0e9a7a79611122efc0",
+            "84c0a4007be04b61bafcef174ec69371",
+            "772ee62e61b74b2d9fcb61c7c2d286f7",
+            "68c533ea901a4c28920b1112b93de258",
+            "c188d0af85324681b5064cdac2ba2f31",
+            "b85ae7b8519640c0a7c9583ed2a8b23f",
+            "df07a8783e864ffd8b772cff27fb5b28",
+            "79a1cb526f4f4a11a940d78b6f3097c4",
+            "a93a629d55334109adaf15782e9065cf",
+            "06b4cbd683da47c8a50afe0065a51151",
+            "472bd364bafb4867a8f9e9f899cbc25e",
+            "e887923a42a942beae899f70429fe491",
+            "3cc7b6773e0543bc836e4595d2ed7bfe",
+            "25be37999c2545ed8c96a2ce60742cee",
+            "a372bd6011b84c45a97e148bdc9695fc",
+            "7cc3464f772b4dacb91f8ce218d342c3",
+            "52804bc114fe46a0b40d553d42a38244",
+            "c76fa847be0746b4b4ee90ab451fc7f6",
+            "a20ccdaa397c4f348b96777cd7f11960",
+            "2b3a85edad614340ba341d2c072d649a",
+            "7f69070804d742cdaae1d2c66563e1ed",
+            "8bf0d5ca3a2c40b6a6d78f419acf5e5a",
+            "4403117d959742f6ae9c6efe6f77ed4f",
+            "6ebd10dc63c34f4ba578409f24149e94",
+            "6edb9d21018a492ba8fb3ea85372946f",
+            "bc89f3e60fa84bf691e9730faa488954",
+            "b4cb31a854374e32bf3f4341c5d3e284",
+            "b247dbbce0654ae8a58aa392c239c39d",
+            "9d6f6ae615aa4fa3a5aed82f7fe1cf8d",
+            "e029ea34ff034b32b76f0a844abb097e",
+            "e8f6511b33bc4013834552ec36806919",
+            "ae11e1bb9b54410290b8274857a8348d",
+            "6ce22946f266497c8a7b96b877a6acfb",
+            "3719bb61e1a3492eb990401878947bac",
+            "c43c34123f644b4682a47526d11d88e2",
+            "68a99f03b6fc4b92971f82d03f7623f0",
+            "77af006fd0f74080a44923315a08acb2",
+            "d3607cb4d41345208edc57807b912e09",
+            "b514a8e63d6d47da8ac3627decef89cc",
+            "2223c3227ba74fc695a3d32f04b829ec",
+            "a849ad5387694694b20a2f703a86bf0d",
+            "f011cc7c7c37423b8e937c6de0481de6",
+            "2ec8db6289e7471c8a71a0ff87b6f8a2",
+            "88d34e1c0cb5447e983b11fb085eb97a",
+            "43c4b99c0d374f13b89e6eee5af8f482",
+            "81f63c0ad2d64e1c86da9f4e763946dc",
+            "9f69f8bea863455b997b0685c9028c3f",
+            "915431f1bd894b86a5a1dea133f7cb3b",
+            "fe522ed5ca7c45a48e3e1c046db6bdba",
+            "37702074c4254f6eb6dc9df61cbb858e",
+            "8b16b87e7c6c4abd82257f56b8972eb3",
+            "6f819b18d65541cfab2be05a7eb8b274",
+            "46ab79f0e8d4499792faa9876f9b3ff0",
+            "0c549289db31454f9671a835cc45f16e",
+            "18ae43ac56a441b1a98f37569fd6d177",
+            "97ec184119fd4af194f16b7a8ecfa053",
+            "14a438bd0f324e4a91866162cc86c85c",
+            "d01d21b04daa491eb39a81ee26a7fc33",
+            "c85e7e8de6864d7398797ac306cfef98",
+            "8aed7f470993413aae78afc0a74b058b",
+            "b60257c0af80409ba7bc7c550e5caa80",
+            "5a1cc2a794654af1bce950fcd542fd15",
+            "3fcf65bf29d1449d88cebbdafea206e9",
+            "7cc17c2030ec4f41ac9e965ff11b14dd",
+            "a2f2db68c9194afca304e70b557b0e8e",
+            "9570c5fefa01420e9bcc38e7385c6649",
+            "63ad5215157d4a8fb0ada9cb86c94f03",
+            "2ce0411a86eb46ac974d0da2f7d0c474",
+            "35cd05d06f4a4bc59437d65b7877a241",
+            "56026e46c26c44e5804e9ffdec4a9ccb",
+            "25efb39f5ea142f084a8696b43fa16cd",
+            "1f6b6f1528534b4e80e5f00ad0c5c0b7",
+            "a7a08996e9c64811b96c5cba473a614b",
+            "a363103e45e94eb0bee2046720ba2130",
+            "2a72200c88c74eb7b1051e2b9e13824d",
+            "82023240560045c1bf1f7dbe870386cf",
+            "aaab672ca574454f95d0efbed97074d2",
+            "6408fe4dd2f24a2ba155aa801ee4d9be",
+            "8019199ec0ce4d878dd6e577e79813dc",
+            "113dc77b9b7d459ea9d7541ec2af46fd",
+            "2c4d26f10efd426f8d023c0560a77841",
+            "bb85706ab5df455f8e73d5fe7c623ca3",
+            "d9f5bc779bfd42dfa03c6a32031255c1",
+            "609d90e62e6743e8b006a975d3383715",
+            "a598b48e927f464e969ad419e46ca555",
+            "679eac02c4244ec7810603c70ddda5a4",
+            "ce458d53331c4a93892cfc23e0fc115a",
+            "048dfd2a045c49439c79734ac42e298f",
+            "d7425e149bbb409080cd7affb8f31652",
+            "ea175e791098454cab0206e0023d9138",
+            "0f7fbd8af9474cb6a00fee4c34d57f3e",
+            "9b7e202889914708b64ca8fd7fb447a2",
+            "0083586e15fa407d822d41a7c11458a4",
+            "b0f38f8eef314a1ca445ca3615b3fe8b",
+            "5955f0ecb8824d78ad43a10695be1cc5",
+            "825c28f81a0548d8a33015be789154bf",
+            "8659f490215949499279c79a88f2f5f6",
+            "443f138f57b7475e86abb0440c7641f1",
+            "134d957583334445a3beed87ed4e73d0",
+            "022c835c4fdd4e70b4b5744139a34efd",
+            "619cfc09f622408e9cca7a75ae6d6932",
+            "10a0663b7fa54385a28fe38ba2dee207",
+            "5deb72b8d7ca4b3da2bb497ca5e96b31",
+            "af97bf4c98d64bea9b1a32bde7295221",
+            "04dba582b14d493583388ac07befa60c",
+            "a40ea53e44144e3cb470d49d81d15727",
+            "33436687b7794410aa29d75217e23dfe",
+            "fb4d7013c5a94b2ab7e277011529a0f2",
+            "4427e78be36242bb8dddd20bb7034922",
+            "92d6ac7839ba423b8c8c8e320b746089",
+            "54a1a6c0c9f04093bbc6119323d76055",
+            "6bcc3429e224490693bf89550210ceb9",
+            "0cb45c3824864477ac81407f43abf97f"
+          ]
+        },
+        "outputId": "d6c8bcbe-b950-4197-b764-c5f395eb8b23"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Unsloth: If you want to finetune Gemma 2, install flash-attn to make it faster!\n",
+            "To install flash-attn, do the below:\n",
+            "\n",
+            "pip install --no-deps --upgrade \"flash-attn>=2.6.3\"\n",
+            "==((====))==  Unsloth 2025.1.7: Fast Gemma2 patching. Transformers: 4.47.1.\n",
+            "   \\\\   /|    GPU: NVIDIA A100-SXM4-40GB. Max memory: 39.564 GB. Platform: Linux.\n",
+            "O^O/ \\_/ \\    Torch: 2.5.1+cu121. CUDA: 8.0. CUDA Toolkit: 12.1. Triton: 3.1.0\n",
+            "\\        /    Bfloat16 = TRUE. FA [Xformers = 0.0.29.post1. FA2 = False]\n",
+            " \"-____-\"     Free Apache license: http://github.com/unslothai/unsloth\n",
+            "Unsloth: Fast downloading is enabled - ignore downloading bars which are red colored!\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "model.safetensors.index.json:   0%|          | 0.00/39.1k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "174f06d96a414316a2312c09f34f712e"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Downloading shards:   0%|          | 0/4 [00:00<?, ?it/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "524de86a695f480eb439a8fd86b21864"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "model-00001-of-00004.safetensors:   0%|          | 0.00/4.90G [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "68c533ea901a4c28920b1112b93de258"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "model-00002-of-00004.safetensors:   0%|          | 0.00/4.95G [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "a372bd6011b84c45a97e148bdc9695fc"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "model-00003-of-00004.safetensors:   0%|          | 0.00/4.96G [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "bc89f3e60fa84bf691e9730faa488954"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "model-00004-of-00004.safetensors:   0%|          | 0.00/3.67G [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "77af006fd0f74080a44923315a08acb2"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Loading checkpoint shards:   0%|          | 0/4 [00:00<?, ?it/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "915431f1bd894b86a5a1dea133f7cb3b"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "generation_config.json:   0%|          | 0.00/190 [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "c85e7e8de6864d7398797ac306cfef98"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "tokenizer_config.json:   0%|          | 0.00/47.0k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "56026e46c26c44e5804e9ffdec4a9ccb"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "tokenizer.model:   0%|          | 0.00/4.24M [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "2c4d26f10efd426f8d023c0560a77841"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "special_tokens_map.json:   0%|          | 0.00/636 [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "9b7e202889914708b64ca8fd7fb447a2"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "tokenizer.json:   0%|          | 0.00/34.4M [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "5deb72b8d7ca4b3da2bb497ca5e96b31"
+            }
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "from unsloth import FastLanguageModel  # FastVisionModel for LLMs\n",
+        "import torch\n",
+        "max_seq_length = 2048  # Choose any! We auto support RoPE Scaling internally!\n",
+        "load_in_4bit = False  # Use 4bit quantization to reduce memory usage. Can be False.\n",
+        "name = \"DrishtiSharma/HINDI-GEMMA-9B-B10\"\n",
+        "model, tokenizer = FastLanguageModel.from_pretrained(\n",
+        "    model_name = name,\n",
+        "    max_seq_length = max_seq_length,\n",
+        "    load_in_4bit = load_in_4bit,\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 56,
+      "id": "b1d480f0-72a7-4150-85ed-0958a40d60ed",
+      "metadata": {
+        "id": "b1d480f0-72a7-4150-85ed-0958a40d60ed",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "320e68bc-827c-4273-9cbc-8d1fcc58f4b1"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "Unsloth 2025.1.7 patched 42 layers with 42 QKV layers, 42 O layers and 42 MLP layers.\n"
+          ]
+        }
+      ],
+      "source": [
+        "model = FastLanguageModel.get_peft_model(\n",
+        "    model,\n",
+        "    r = 16, # Choose any number > 0 ! Suggested 8, 16, 32, 64, 128\n",
+        "    target_modules = [\"q_proj\", \"k_proj\", \"v_proj\", \"o_proj\",\n",
+        "                      \"gate_proj\", \"up_proj\", \"down_proj\",],\n",
+        "    lora_alpha = 16,\n",
+        "    lora_dropout = 0, # Supports any, but = 0 is optimized\n",
+        "    bias = \"none\",    # Supports any, but = \"none\" is optimized\n",
+        "    # [NEW] \"unsloth\" uses 30% less VRAM, fits 2x larger batch sizes!\n",
+        "    use_gradient_checkpointing = \"unsloth\", # True or \"unsloth\" for very long context\n",
+        "    random_state = 3407,\n",
+        "    use_rslora = False,  # We support rank stabilized LoRA\n",
+        "    loftq_config = None, # And LoftQ\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 57,
+      "id": "35603404-a7a0-4f24-92de-fd778500df99",
+      "metadata": {
+        "id": "35603404-a7a0-4f24-92de-fd778500df99",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "a5191689-c7d9-4500-dab1-8d7991d4bdbd"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Requirement already satisfied: datasets in /usr/local/lib/python3.11/dist-packages (3.2.0)\n",
+            "Requirement already satisfied: tqdm in /usr/local/lib/python3.11/dist-packages (4.67.1)\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from datasets) (3.17.0)\n",
+            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.11/dist-packages (from datasets) (1.26.4)\n",
+            "Requirement already satisfied: pyarrow>=15.0.0 in /usr/local/lib/python3.11/dist-packages (from datasets) (17.0.0)\n",
+            "Requirement already satisfied: dill<0.3.9,>=0.3.0 in /usr/local/lib/python3.11/dist-packages (from datasets) (0.3.8)\n",
+            "Requirement already satisfied: pandas in /usr/local/lib/python3.11/dist-packages (from datasets) (2.2.2)\n",
+            "Requirement already satisfied: requests>=2.32.2 in /usr/local/lib/python3.11/dist-packages (from datasets) (2.32.3)\n",
+            "Requirement already satisfied: xxhash in /usr/local/lib/python3.11/dist-packages (from datasets) (3.5.0)\n",
+            "Requirement already satisfied: multiprocess<0.70.17 in /usr/local/lib/python3.11/dist-packages (from datasets) (0.70.16)\n",
+            "Requirement already satisfied: fsspec<=2024.9.0,>=2023.1.0 in /usr/local/lib/python3.11/dist-packages (from fsspec[http]<=2024.9.0,>=2023.1.0->datasets) (2024.9.0)\n",
+            "Requirement already satisfied: aiohttp in /usr/local/lib/python3.11/dist-packages (from datasets) (3.11.11)\n",
+            "Requirement already satisfied: huggingface-hub>=0.23.0 in /usr/local/lib/python3.11/dist-packages (from datasets) (0.27.1)\n",
+            "Requirement already satisfied: packaging in /usr/local/lib/python3.11/dist-packages (from datasets) (24.2)\n",
+            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.11/dist-packages (from datasets) (6.0.2)\n",
+            "Requirement already satisfied: aiohappyeyeballs>=2.3.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (2.4.4)\n",
+            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (1.3.2)\n",
+            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (24.3.0)\n",
+            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (1.5.0)\n",
+            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (6.1.0)\n",
+            "Requirement already satisfied: propcache>=0.2.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (0.2.1)\n",
+            "Requirement already satisfied: yarl<2.0,>=1.17.0 in /usr/local/lib/python3.11/dist-packages (from aiohttp->datasets) (1.18.3)\n",
+            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.23.0->datasets) (4.12.2)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets) (3.4.1)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets) (3.10)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets) (2.3.0)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests>=2.32.2->datasets) (2024.12.14)\n",
+            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.11/dist-packages (from pandas->datasets) (2.8.2)\n",
+            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.11/dist-packages (from pandas->datasets) (2024.2)\n",
+            "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.11/dist-packages (from pandas->datasets) (2025.1)\n",
+            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.11/dist-packages (from python-dateutil>=2.8.2->pandas->datasets) (1.17.0)\n"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install datasets tqdm\n",
+        "import pandas as pd\n",
+        "from datasets import load_dataset\n",
+        "import os"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 58,
+      "id": "2c49fafe-1e9a-4e29-8d85-94ff79f8c9c0",
+      "metadata": {
+        "id": "2c49fafe-1e9a-4e29-8d85-94ff79f8c9c0"
+      },
+      "outputs": [],
+      "source": [
+        "FastLanguageModel.for_inference(model)\n",
+        "from tqdm import tqdm\n",
+        "tqdm.pandas()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 59,
+      "id": "1749c745-d1fb-430b-9469-4913bb2a6cb5",
+      "metadata": {
+        "id": "1749c745-d1fb-430b-9469-4913bb2a6cb5",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 441
+        },
+        "outputId": "2f687264-eede-43da-9cec-523b97a16fa8"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "14042\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                                                   Input Output  \\\n",
+              "0      Q पर दिए गए क्षेत्र विस्तार Q(sqrt(2), sqrt(3)...      B   \n",
+              "1      मान लीजिए S_5 में p = (1, 2, 5, 4)(2, 3) है. S...      C   \n",
+              "2      दिए गए बहुपद के संकेतित परिमित क्षेत्र में गुण...      D   \n",
+              "3      कथन 1 | नॉन-एबेलियन ग्रुप का एक फ़ैक्टर ग्रुप ...      B   \n",
+              "4      दिए गए बहुपद रिंग में दिए गए बहुपदों का गुणनफल...      B   \n",
+              "...                                                  ...    ...   \n",
+              "14037  चीन और कोरिया में धार्मिक परम्पराओं का मुख्य क...      A   \n",
+              "14038  हान राजवंश के समय सूखे के दौरान आम लोग किससे अ...      C   \n",
+              "14039  धर्मशास्त्रीय शब्द होमोओसिओस का अर्थ निम्नलिखि...      B   \n",
+              "14040  जापानी मूल मिथक के अनुसार, अमातरासु को किसने अ...      B   \n",
+              "14041  ऑगस्टस का नुमेन निम्नलिखित में से किस विशेषता ...      A   \n",
+              "\n",
+              "             Sub-Domain Dataset  \n",
+              "0      abstract_algebra    MMLU  \n",
+              "1      abstract_algebra    MMLU  \n",
+              "2      abstract_algebra    MMLU  \n",
+              "3      abstract_algebra    MMLU  \n",
+              "4      abstract_algebra    MMLU  \n",
+              "...                 ...     ...  \n",
+              "14037   world_religions    MMLU  \n",
+              "14038   world_religions    MMLU  \n",
+              "14039   world_religions    MMLU  \n",
+              "14040   world_religions    MMLU  \n",
+              "14041   world_religions    MMLU  \n",
+              "\n",
+              "[14042 rows x 4 columns]"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-d47d7ddd-fa69-47d2-8dff-7de7fa9dfa94\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Input</th>\n",
+              "      <th>Output</th>\n",
+              "      <th>Sub-Domain</th>\n",
+              "      <th>Dataset</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>Q पर दिए गए क्षेत्र विस्तार Q(sqrt(2), sqrt(3)...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>abstract_algebra</td>\n",
+              "      <td>MMLU</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>मान लीजिए S_5 में p = (1, 2, 5, 4)(2, 3) है. S...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>abstract_algebra</td>\n",
+              "      <td>MMLU</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>दिए गए बहुपद के संकेतित परिमित क्षेत्र में गुण...</td>\n",
+              "      <td>D</td>\n",
+              "      <td>abstract_algebra</td>\n",
+              "      <td>MMLU</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>कथन 1 | नॉन-एबेलियन ग्रुप का एक फ़ैक्टर ग्रुप ...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>abstract_algebra</td>\n",
+              "      <td>MMLU</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>दिए गए बहुपद रिंग में दिए गए बहुपदों का गुणनफल...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>abstract_algebra</td>\n",
+              "      <td>MMLU</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>14037</th>\n",
+              "      <td>चीन और कोरिया में धार्मिक परम्पराओं का मुख्य क...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>world_religions</td>\n",
+              "      <td>MMLU</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>14038</th>\n",
+              "      <td>हान राजवंश के समय सूखे के दौरान आम लोग किससे अ...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>world_religions</td>\n",
+              "      <td>MMLU</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>14039</th>\n",
+              "      <td>धर्मशास्त्रीय शब्द होमोओसिओस का अर्थ निम्नलिखि...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>world_religions</td>\n",
+              "      <td>MMLU</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>14040</th>\n",
+              "      <td>जापानी मूल मिथक के अनुसार, अमातरासु को किसने अ...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>world_religions</td>\n",
+              "      <td>MMLU</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>14041</th>\n",
+              "      <td>ऑगस्टस का नुमेन निम्नलिखित में से किस विशेषता ...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>world_religions</td>\n",
+              "      <td>MMLU</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>14042 rows × 4 columns</p>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d47d7ddd-fa69-47d2-8dff-7de7fa9dfa94')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-d47d7ddd-fa69-47d2-8dff-7de7fa9dfa94 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-d47d7ddd-fa69-47d2-8dff-7de7fa9dfa94');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-b3d3defd-32bb-44f4-9f5a-571510140904\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-b3d3defd-32bb-44f4-9f5a-571510140904')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-b3d3defd-32bb-44f4-9f5a-571510140904 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "\n",
+              "  <div id=\"id_79d80682-e926-42fc-8131-f8dfcfc08f02\">\n",
+              "    <style>\n",
+              "      .colab-df-generate {\n",
+              "        background-color: #E8F0FE;\n",
+              "        border: none;\n",
+              "        border-radius: 50%;\n",
+              "        cursor: pointer;\n",
+              "        display: none;\n",
+              "        fill: #1967D2;\n",
+              "        height: 32px;\n",
+              "        padding: 0 0 0 0;\n",
+              "        width: 32px;\n",
+              "      }\n",
+              "\n",
+              "      .colab-df-generate:hover {\n",
+              "        background-color: #E2EBFA;\n",
+              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "        fill: #174EA6;\n",
+              "      }\n",
+              "\n",
+              "      [theme=dark] .colab-df-generate {\n",
+              "        background-color: #3B4455;\n",
+              "        fill: #D2E3FC;\n",
+              "      }\n",
+              "\n",
+              "      [theme=dark] .colab-df-generate:hover {\n",
+              "        background-color: #434B5C;\n",
+              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "        fill: #FFFFFF;\n",
+              "      }\n",
+              "    </style>\n",
+              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
+              "            title=\"Generate code using this dataframe.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "    <script>\n",
+              "      (() => {\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#id_79d80682-e926-42fc-8131-f8dfcfc08f02 button.colab-df-generate');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      buttonEl.onclick = () => {\n",
+              "        google.colab.notebook.generateWithVariable('df');\n",
+              "      }\n",
+              "      })();\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "variable_name": "df",
+              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 14042,\n  \"fields\": [\n    {\n      \"column\": \"Input\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 13981,\n        \"samples\": [\n          \"\\u092c\\u0941\\u0928\\u094d\\u092f\\u093e\\u0935\\u093e\\u092f\\u0930\\u0938 \\u092a\\u0930\\u093f\\u0935\\u093e\\u0930 \\u0915\\u0940 \\u090f\\u0915 \\u092a\\u094d\\u0930\\u092e\\u0941\\u0916 \\u0935\\u093f\\u0936\\u0947\\u0937\\u0924\\u093e \\u0915\\u094c\\u0928 \\u0938\\u0940 \\u0939\\u0948? ###  A) \\u092c\\u094c\\u0928\\u094b\\u0902, \\u092e\\u091a\\u094d\\u091b\\u0930\\u094b\\u0902, \\u0930\\u0947\\u0924 \\u0915\\u0940 \\u092e\\u0915\\u094d\\u0916\\u093f\\u092f\\u094b\\u0902, \\u0915\\u0941\\u091f\\u0915\\u0940 \\u0915\\u0947 \\u0932\\u0917\\u093e\\u0924\\u093e\\u0930 \\u0938\\u0902\\u0915\\u094d\\u0930\\u092e\\u0923 \\u0938\\u0947 \\u092c\\u0922\\u093c\\u0928\\u093e B) \\u092e\\u0941\\u0916\\u094d\\u092f \\u0930\\u0942\\u092a \\u0938\\u0947 \\u092e\\u091a\\u094d\\u091b\\u0930\\u094b\\u0902 \\u0938\\u0947 \\u092b\\u0948\\u0932\\u0928\\u093e C) \\u0906\\u0928\\u0941\\u0935\\u0902\\u0936\\u093f\\u0915 \\u092a\\u0941\\u0928\\u0930\\u094d\\u0938\\u0902\\u092f\\u094b\\u091c\\u0928 \\u092f\\u093e \\u092a\\u0941\\u0928\\u0930\\u094d\\u0935\\u093f\\u0928\\u094d\\u092f\\u093e\\u0938 D) \\u091a\\u0942\\u0939\\u094b\\u0902 \\u0915\\u0947 \\u0915\\u093e\\u091f\\u0928\\u0947 \\u0938\\u0947 \\u092e\\u0928\\u0941\\u0937\\u094d\\u092f\\u094b\\u0902 \\u092e\\u0947\\u0902 \\u092b\\u0948\\u0932\\u093e\\u0935 ### MCQ ### \",\n          \"70 \\u0935\\u0930\\u094d\\u0937\\u0940\\u092f \\u090f\\u0915 \\u092e\\u0939\\u093f\\u0932\\u093e \\u0905\\u092a\\u0928\\u0947 \\u0939\\u093e\\u0925\\u094b\\u0902 \\u0915\\u0947 \\u0915\\u0902\\u092a\\u0928 \\u0915\\u0940 \\u0938\\u092e\\u0938\\u094d\\u092f\\u093e \\u0915\\u0947 \\u0915\\u093e\\u0930\\u0923 \\u0915\\u093e\\u0930\\u094d\\u092f\\u093e\\u0932\\u092f \\u0906\\u0924\\u0940 \\u0939\\u0948\\u0964 \\u092f\\u0939 \\u0915\\u0902\\u092a\\u0928 \\u0909\\u0938\\u0915\\u0947 \\u091c\\u0940\\u0935\\u0928 \\u0915\\u0947 \\u0905\\u0927\\u093f\\u0915\\u093e\\u0902\\u0936 \\u0938\\u092e\\u092f \\u0938\\u0947 \\u092e\\u094c\\u091c\\u0942\\u0926 \\u0939\\u0948 \\u0914\\u0930 \\u0936\\u0941\\u0930\\u0942 \\u092e\\u0947\\u0902 \\u0939\\u0932\\u094d\\u0915\\u093e \\u0925\\u093e \\u0914\\u0930 \\u0915\\u0947\\u0935\\u0932 \\u0924\\u092d\\u0940 \\u0939\\u094b\\u0924\\u093e \\u0925\\u093e \\u091c\\u092c \\u0935\\u0939 \\u0925\\u0915\\u0940 \\u0939\\u0941\\u0908 \\u092f\\u093e \\u0924\\u0928\\u093e\\u0935\\u0917\\u094d\\u0930\\u0938\\u094d\\u0924 \\u0939\\u094b\\u0924\\u0940 \\u0925\\u0940\\u0964 \\u092a\\u093f\\u091b\\u0932\\u0947 \\u092e\\u0939\\u0940\\u0928\\u0947 \\u0915\\u0947 \\u0926\\u094c\\u0930\\u093e\\u0928 \\u0915\\u0902\\u092a\\u0928 \\u0905\\u0927\\u093f\\u0915 \\u0927\\u094d\\u092f\\u093e\\u0928 \\u0926\\u0947\\u0928\\u0947 \\u092f\\u094b\\u0917\\u094d\\u092f \\u0914\\u0930 \\u0932\\u0917\\u093e\\u0924\\u093e\\u0930 \\u0939\\u094b \\u0917\\u092f\\u093e \\u0939\\u0948\\u0964 \\u0915\\u0902\\u092a\\u0928 \\u0915\\u0940 \\u0938\\u092e\\u0938\\u094d\\u092f\\u093e \\u0915\\u0947 \\u0915\\u093e\\u0930\\u0923 \\u0905\\u092c \\u0935\\u0939 \\u0905\\u0928\\u094d\\u092f \\u0932\\u094b\\u0917\\u094b\\u0902 \\u0915\\u0947 \\u0938\\u093e\\u0925 \\u0916\\u093e\\u0928\\u0947 \\u092e\\u0947\\u0902 \\u0936\\u0930\\u094d\\u092e \\u092e\\u0939\\u0938\\u0942\\u0938 \\u0915\\u0930\\u0924\\u0940 \\u0939\\u0948\\u0964\\u092e\\u0930\\u0940\\u091c \\u092a\\u093f\\u091b\\u0932\\u0947 3 \\u0938\\u092a\\u094d\\u0924\\u093e\\u0939 \\u0938\\u0947 \\u092b\\u094d\\u0932\\u0941\\u0913\\u0915\\u094d\\u0938\\u0947\\u091f\\u0940\\u0928 \\u0932\\u0947 \\u0930\\u0939\\u0940 \\u0939\\u0948 \\u0924\\u093e\\u0915\\u093f 2 \\u092e\\u0939\\u0940\\u0928\\u0947 \\u092a\\u0939\\u0932\\u0947 \\u0909\\u0938\\u0915\\u0947 \\u092a\\u0924\\u093f \\u0915\\u0940 \\u092e\\u0943\\u0924\\u094d\\u092f\\u0941 \\u0938\\u0947 \\u0909\\u092c\\u0930\\u0928\\u0947 \\u092e\\u0947\\u0902 \\u0909\\u0938\\u0947 \\u092e\\u0926\\u0926 \\u092e\\u093f\\u0932 \\u0938\\u0915\\u0947\\u0964 \\u0932\\u093f\\u0938\\u093f\\u0928\\u094b\\u092a\\u094d\\u0930\\u093f\\u0932 \\u0938\\u0947 \\u0928\\u093f\\u092f\\u0902\\u0924\\u094d\\u0930\\u093f\\u0924 \\u0906\\u0935\\u0936\\u094d\\u092f\\u0915 \\u0909\\u091a\\u094d\\u091a \\u0930\\u0915\\u094d\\u0924\\u091a\\u093e\\u092a \\u0914\\u0930 \\u090f\\u091f\\u094b\\u0930\\u0935\\u093e\\u0938\\u094d\\u091f\\u0947\\u091f\\u093f\\u0928 \\u0938\\u0947 \\u0928\\u093f\\u092f\\u0902\\u0924\\u094d\\u0930\\u093f\\u0924 \\u0939\\u093e\\u0907\\u092a\\u0930\\u0932\\u093f\\u092a\\u093f\\u0921\\u093f\\u092e\\u093f\\u092f\\u093e \\u0915\\u0947 \\u0932\\u093f\\u090f \\u091a\\u093f\\u0915\\u093f\\u0924\\u094d\\u0938\\u093e \\u0907\\u0924\\u093f\\u0939\\u093e\\u0938 \\u092d\\u0940 \\u0909\\u0932\\u094d\\u0932\\u0947\\u0916\\u0928\\u0940\\u092f \\u0939\\u0948\\u0964 \\u091c\\u094b\\u0921\\u093c\\u094b\\u0902 \\u0915\\u0947 \\u0926\\u0930\\u094d\\u0926 \\u0915\\u0947 \\u0932\\u093f\\u090f \\u0909\\u0938\\u0915\\u0940 \\u090f\\u0915\\u092e\\u093e\\u0924\\u094d\\u0930 \\u0905\\u0928\\u094d\\u092f \\u0926\\u0935\\u093e \\u0915\\u092d\\u0940-\\u0915\\u092d\\u0940 \\u0907\\u092c\\u0941\\u092a\\u094d\\u0930\\u094b\\u092b\\u0947\\u0928 \\u0939\\u0948\\u0964 \\u0935\\u0939 \\u092e\\u0939\\u0940\\u0928\\u0947 \\u092e\\u0947\\u0902 \\u090f\\u0915 \\u0938\\u0947 \\u0926\\u094b \\u092c\\u093e\\u0930 \\u0936\\u0930\\u093e\\u092c \\u092a\\u0940\\u0924\\u0940 \\u0925\\u0940 \\u0932\\u0947\\u0915\\u093f\\u0928 \\u0905\\u092c \\u0935\\u0939 \\u0930\\u094b\\u091c\\u093e\\u0928\\u093e \\u090f\\u0915 \\u0917\\u093f\\u0932\\u093e\\u0938 \\u0935\\u093e\\u0907\\u0928 \\u092a\\u0940\\u0924\\u0940 \\u0939\\u0948 \\u0915\\u094d\\u092f\\u094b\\u0902\\u0915\\u093f, \\u0909\\u0938\\u0915\\u093e \\u0915\\u0939\\u0928\\u093e \\u0939\\u0948 \\u0915\\u093f \\u0907\\u0938\\u0938\\u0947 \\u0909\\u0938\\u0915\\u093e \\u0915\\u0902\\u092a\\u0928 \\u0915\\u092e \\u0939\\u094b\\u0924\\u093e \\u0939\\u0948\\u0964 \\u0909\\u0938\\u0915\\u0940 \\u0932\\u0902\\u092c\\u093e\\u0908 168 \\u0938\\u0947\\u092e\\u0940 (5 \\u092b\\u0940\\u091f 6 \\u0907\\u0902\\u091a) \\u0939\\u0948 \\u0914\\u0930 \\u0909\\u0938\\u0915\\u093e \\u0935\\u091c\\u0928 70 \\u0915\\u093f\\u0932\\u094b\\u0917\\u094d\\u0930\\u093e\\u092e (155 \\u092a\\u093e\\u0909\\u0902\\u0921) \\u0939\\u0948; \\u092c\\u0940\\u090f\\u092e\\u0906\\u0908 25 \\u0915\\u093f\\u0932\\u094b\\u0917\\u094d\\u0930\\u093e\\u092e/\\u092e\\u09402 \\u0939\\u0948\\u0964 \\u092e\\u0939\\u0924\\u094d\\u0935\\u092a\\u0942\\u0930\\u094d\\u0923 \\u0938\\u0902\\u0915\\u0947\\u0924 \\u0939\\u0948\\u0902 \\u0924\\u093e\\u092a\\u092e\\u093e\\u0928 36.4\\u00b0C (97.6\\u00b0F), \\u0928\\u093e\\u0921\\u093c\\u0940 80/\\u092e\\u093f\\u0928\\u091f, \\u0936\\u094d\\u0935\\u0938\\u0928 18/\\u092e\\u093f\\u0928\\u091f, \\u0924\\u0925\\u093e \\u0930\\u0915\\u094d\\u0924\\u091a\\u093e\\u092a 130/85 mm Hg. \\u0936\\u093e\\u0930\\u0940\\u0930\\u093f\\u0915 \\u092a\\u0930\\u0940\\u0915\\u094d\\u0937\\u0923 \\u0938\\u0947 \\u0926\\u094b\\u0928\\u094b\\u0902 \\u0939\\u093e\\u0925\\u094b\\u0902 \\u092e\\u0947\\u0902 \\u092e\\u0927\\u094d\\u092f\\u092e \\u0915\\u0902\\u092a\\u0928 \\u0926\\u093f\\u0916\\u093e\\u0908 \\u0926\\u0947\\u0924\\u093e \\u0939\\u0948 \\u091c\\u094b \\u0906\\u0930\\u093e\\u092e \\u0915\\u0947 \\u0938\\u092e\\u092f \\u0928\\u0939\\u0940\\u0902 \\u0939\\u094b\\u0924\\u093e\\u0964 \\u092a\\u0942\\u0930\\u094d\\u0923 \\u0930\\u0915\\u094d\\u0924 \\u0917\\u0923\\u0928\\u093e, \\u0938\\u0940\\u0930\\u092e \\u0930\\u0938\\u093e\\u092f\\u0928 \\u092a\\u094d\\u0930\\u094b\\u092b\\u093c\\u093e\\u0907\\u0932, \\u0924\\u0925\\u093e \\u0938\\u0940\\u0930\\u092e \\u0925\\u093e\\u092f\\u0930\\u0949\\u092f\\u0921 \\u092b\\u093c\\u0902\\u0915\\u094d\\u0936\\u0928 \\u092a\\u0930\\u0940\\u0915\\u094d\\u0937\\u0923 \\u0915\\u093e \\u0906\\u0926\\u0947\\u0936 \\u0926\\u093f\\u092f\\u093e \\u0917\\u092f\\u093e \\u0939\\u0948 \\u0924\\u0925\\u093e \\u092a\\u0930\\u093f\\u0923\\u093e\\u092e \\u0932\\u0902\\u092c\\u093f\\u0924 \\u0939\\u0948\\u0902\\u0964 \\u0930\\u094b\\u0917\\u0940 \\u0915\\u0947 \\u0915\\u0902\\u092a\\u0928 \\u0915\\u0947 \\u092c\\u093f\\u0917\\u0921\\u093c\\u0928\\u0947 \\u0915\\u093e \\u0938\\u092c\\u0938\\u0947 \\u0938\\u0902\\u092d\\u093e\\u0935\\u093f\\u0924 \\u0915\\u093e\\u0930\\u0923 \\u0928\\u093f\\u092e\\u094d\\u0928\\u0932\\u093f\\u0916\\u093f\\u0924 \\u092e\\u0947\\u0902 \\u0938\\u0947 \\u0915\\u094c\\u0928 \\u0938\\u093e \\u0939\\u0948? ###  A) \\u092b\\u094d\\u0932\\u0941\\u0913\\u0915\\u094d\\u0938\\u0947\\u091f\\u0940\\u0928 \\u0925\\u0947\\u0930\\u0947\\u092a\\u0940 \\u0915\\u093e \\u092a\\u094d\\u0930\\u0924\\u093f\\u0915\\u0942\\u0932 \\u092a\\u094d\\u0930\\u092d\\u093e\\u0935 B) \\u0936\\u094b\\u0915 \\u092a\\u094d\\u0930\\u0924\\u093f\\u0915\\u094d\\u0930\\u093f\\u092f\\u093e C) \\u092a\\u094d\\u0930\\u093e\\u0930\\u0902\\u092d\\u093f\\u0915 \\u092a\\u093e\\u0930\\u094d\\u0915\\u093f\\u0902\\u0938\\u0928 \\u0930\\u094b\\u0917 D) \\u0936\\u0930\\u093e\\u092c \\u0915\\u0940 \\u0916\\u092a\\u0924 \\u092e\\u0947\\u0902 \\u0935\\u0943\\u0926\\u094d\\u0927\\u093f ### MCQ ### \",\n          \"\\u0932\\u0917\\u092d\\u0917 \\u0915\\u093f\\u0924\\u0928\\u0947 \\u0936\\u094b\\u0915\\u0917\\u094d\\u0930\\u0938\\u094d\\u0924 \\u0935\\u094d\\u092f\\u0915\\u094d\\u0924\\u093f\\u092f\\u094b\\u0902 \\u0915\\u094b \\u0915\\u0941\\u091b \\u092a\\u0947\\u0936\\u0947\\u0935\\u0930 \\u092e\\u0926\\u0926 \\u0915\\u0940 \\u0906\\u0935\\u0936\\u094d\\u092f\\u0915\\u0924\\u093e \\u0939\\u094b\\u0924\\u0940 \\u0939\\u0948? ###  A) 10% \\u0938\\u0947 \\u0915\\u092e B) \\u0932\\u0917\\u092d\\u0917 25% C) \\u0932\\u0917\\u092d\\u0917 \\u0906\\u0927\\u0947 D) 50% \\u0938\\u0947 \\u0905\\u0927\\u093f\\u0915 ### MCQ ### \"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Output\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"C\",\n          \"A\",\n          \"B\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sub-Domain\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 57,\n        \"samples\": [\n          \"abstract_algebra\",\n          \"college_biology\",\n          \"high_school_us_history\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Dataset\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"MMLU\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 59
+        }
+      ],
+      "source": [
+        "dataset = load_dataset(\"1-800-LLMs/Test-Collection\", data_files=\"MMMLU_H.csv\", split=\"train\")\n",
+        "df = dataset.to_pandas()\n",
+        "print(len(df))\n",
+        "df"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 60,
+      "id": "251f9198-60d4-4ec1-88a8-f344234be2de",
+      "metadata": {
+        "id": "251f9198-60d4-4ec1-88a8-f344234be2de"
+      },
+      "outputs": [],
+      "source": [
+        "df['tok'] = df['Input'].apply(lambda x: len(tokenizer.encode(x)))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 61,
+      "id": "dbffda0c-e536-4891-8862-e1e5936eb6be",
+      "metadata": {
+        "id": "dbffda0c-e536-4891-8862-e1e5936eb6be",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "352c1273-13a0-4709-a844-4476a3e472e7"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Average 'tok' value: 180.577624270047\n",
+            "Max 'tok' value: 1917\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(f\"Average 'tok' value: {df['tok'].mean()}\")\n",
+        "print(f\"Max 'tok' value: {df['tok'].max()}\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 62,
+      "id": "9409ad7f-697c-4533-8d2f-399928ca9033",
+      "metadata": {
+        "id": "9409ad7f-697c-4533-8d2f-399928ca9033"
+      },
+      "outputs": [],
+      "source": [
+        "df = df.sort_values('tok', ascending=False)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 63,
+      "id": "26544979-f1f2-4622-be64-9f8559a99460",
+      "metadata": {
+        "id": "26544979-f1f2-4622-be64-9f8559a99460",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "de543a99-9e37-410e-f42c-d24629b153d9"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.11/dist-packages (3.10.0)\n",
+            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (1.3.1)\n",
+            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (0.12.1)\n",
+            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (4.55.5)\n",
+            "Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (1.4.8)\n",
+            "Requirement already satisfied: numpy>=1.23 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (1.26.4)\n",
+            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (24.2)\n",
+            "Requirement already satisfied: pillow>=8 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (11.1.0)\n",
+            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (3.2.1)\n",
+            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.11/dist-packages (from matplotlib) (2.8.2)\n",
+            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.11/dist-packages (from python-dateutil>=2.7->matplotlib) (1.17.0)\n"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install matplotlib"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 64,
+      "id": "8ce90df6-271e-460b-97fe-30a2480c78b6",
+      "metadata": {
+        "id": "8ce90df6-271e-460b-97fe-30a2480c78b6",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 564
+        },
+        "outputId": "ed4e326c-1991-4a98-c63d-5e76c9c67608"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1000x600 with 1 Axes>"
+            ],
+            "image/png": "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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "import matplotlib.pyplot as plt\n",
+        "plt.figure(figsize=(10, 6))\n",
+        "plt.plot(df['tok'].values, marker='o', linestyle='-')\n",
+        "plt.xlabel('Sorted Entry Index')\n",
+        "plt.ylabel('Token Count')\n",
+        "plt.title(\"Line Plot of Token Counts (Sorted Ascending)\")\n",
+        "plt.grid(True)\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 65,
+      "id": "01127bdd-aa73-4118-a5b8-53e5ed709bf5",
+      "metadata": {
+        "id": "01127bdd-aa73-4118-a5b8-53e5ed709bf5",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 363
+        },
+        "outputId": "0931d84d-0b77-433b-cbc7-8037bcc8ea41"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                                                   Input Output  \\\n",
+              "1262   सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...      B   \n",
+              "1202   सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...      A   \n",
+              "1289   सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...      A   \n",
+              "1246   सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...      D   \n",
+              "1358   सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...      D   \n",
+              "5938   यह प्रश्न निम्नलिखित जानकारी से संबंधित है।\\nस...      A   \n",
+              "5874   यह प्रश्न निम्नलिखित जानकारी से संबंधित है।\\nस...      B   \n",
+              "12115  साल 1993 में, एक पशुपालक किसान को 20 एकड़ के स...      A   \n",
+              "10876  एक भूमि-विकास कंपनी के पास दक्षिणपश्चिम में 40...      C   \n",
+              "11923  साल 1993 में, एक ज़मींदार के पास एक अंगूर के ब...      C   \n",
+              "\n",
+              "                      Sub-Domain Dataset   tok  \n",
+              "1262            college_medicine    MMLU  1917  \n",
+              "1202            college_medicine    MMLU  1894  \n",
+              "1289            college_medicine    MMLU  1892  \n",
+              "1246            college_medicine    MMLU  1831  \n",
+              "1358            college_medicine    MMLU  1830  \n",
+              "5938   high_school_world_history    MMLU  1313  \n",
+              "5874   high_school_world_history    MMLU  1292  \n",
+              "12115           professional_law    MMLU  1279  \n",
+              "10876           professional_law    MMLU  1277  \n",
+              "11923           professional_law    MMLU  1266  "
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-df896ece-8dec-4d91-9128-aedd06c1199e\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Input</th>\n",
+              "      <th>Output</th>\n",
+              "      <th>Sub-Domain</th>\n",
+              "      <th>Dataset</th>\n",
+              "      <th>tok</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>1262</th>\n",
+              "      <td>सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>college_medicine</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1917</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1202</th>\n",
+              "      <td>सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>college_medicine</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1894</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1289</th>\n",
+              "      <td>सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>college_medicine</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1892</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1246</th>\n",
+              "      <td>सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...</td>\n",
+              "      <td>D</td>\n",
+              "      <td>college_medicine</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1831</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1358</th>\n",
+              "      <td>सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...</td>\n",
+              "      <td>D</td>\n",
+              "      <td>college_medicine</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1830</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5938</th>\n",
+              "      <td>यह प्रश्न निम्नलिखित जानकारी से संबंधित है।\\nस...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>high_school_world_history</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1313</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5874</th>\n",
+              "      <td>यह प्रश्न निम्नलिखित जानकारी से संबंधित है।\\nस...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>high_school_world_history</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1292</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>12115</th>\n",
+              "      <td>साल 1993 में, एक पशुपालक किसान को 20 एकड़ के स...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>professional_law</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1279</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>10876</th>\n",
+              "      <td>एक भूमि-विकास कंपनी के पास दक्षिणपश्चिम में 40...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>professional_law</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1277</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>11923</th>\n",
+              "      <td>साल 1993 में, एक ज़मींदार के पास एक अंगूर के ब...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>professional_law</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1266</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-df896ece-8dec-4d91-9128-aedd06c1199e')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-df896ece-8dec-4d91-9128-aedd06c1199e button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-df896ece-8dec-4d91-9128-aedd06c1199e');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-8d896083-fab4-42d1-ae07-173deaf6d468\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-8d896083-fab4-42d1-ae07-173deaf6d468')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-8d896083-fab4-42d1-ae07-173deaf6d468 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "variable_name": "df",
+              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 14042,\n  \"fields\": [\n    {\n      \"column\": \"Input\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 13981,\n        \"samples\": [\n          \"\\u0928\\u093f\\u092e\\u094d\\u0928\\u0932\\u093f\\u0916\\u093f\\u0924 \\u092e\\u0947\\u0902 \\u0938\\u0947 \\u0915\\u093f\\u0938 \\u092a\\u0926\\u093e\\u0930\\u094d\\u0925 \\u0915\\u0940 \\u0906\\u0923\\u094d\\u0935\\u093f\\u0915 \\u0938\\u0902\\u0930\\u091a\\u0928\\u093e \\u0905\\u0938\\u092e\\u092e\\u093f\\u0924 \\u0939\\u094b\\u0924\\u0940 \\u0939\\u0948? ###  A) SF4 B) PCl5 C) BF3 D) CO2 ### MCQ ### \",\n          \"\\u090f\\u0915\\u094d\\u0935\\u093f\\u0928\\u093e\\u0938 \\u0915\\u093e \\u0928\\u0948\\u0924\\u093f\\u0915 \\u0938\\u093f\\u0926\\u094d\\u0927\\u093e\\u0902\\u0924 \\u092a\\u094d\\u0930\\u093e\\u0915\\u0943\\u0924\\u093f\\u0915 \\u0915\\u093e\\u0928\\u0942\\u0928 \\u0938\\u093f\\u0926\\u094d\\u0927\\u093e\\u0902\\u0924  ###  A) \\u092a\\u0930\\u093f\\u0923\\u093e\\u092e\\u0935\\u093e\\u0926\\u0964 B) \\u0915\\u093e \\u090f\\u0915 \\u0938\\u0902\\u0938\\u094d\\u0915\\u0930\\u0923 \\u0939\\u0948\\u0964 C) \\u0905\\u0927\\u093f\\u0915\\u093e\\u0930-\\u0906\\u0927\\u093e\\u0930\\u093f\\u0924 \\u0938\\u093f\\u0926\\u094d\\u0927\\u093e\\u0902\\u0924. D) \\u092a\\u0941\\u0923\\u094d\\u092f \\u0928\\u0948\\u0924\\u093f\\u0915\\u0924\\u093e\\u0964 ### MCQ ### \",\n          \"\\u091c\\u093f\\u0938 \\u0926\\u0930 \\u092a\\u0930 \\u0936\\u0941\\u0926\\u094d\\u0927\\u093f\\u0915\\u0930\\u0923 \\u092a\\u094d\\u0930\\u0915\\u094d\\u0930\\u093f\\u092f\\u093e \\u092a\\u093e\\u0928\\u0940 \\u0915\\u0947 \\u091f\\u0948\\u0902\\u0915 \\u0938\\u0947 \\u0926\\u0942\\u0937\\u093f\\u0924 \\u092a\\u0926\\u093e\\u0930\\u094d\\u0925\\u094b\\u0902 \\u0915\\u094b \\u0939\\u091f\\u093e \\u0938\\u0915\\u0924\\u0940 \\u0939\\u0948, \\u0935\\u0939 \\u0936\\u0947\\u0937 \\u0926\\u0942\\u0937\\u093f\\u0924 \\u092a\\u0926\\u093e\\u0930\\u094d\\u0925\\u094b\\u0902 \\u0915\\u0940 \\u092e\\u093e\\u0924\\u094d\\u0930\\u093e \\u0915\\u0947 \\u0938\\u092e\\u093e\\u0928\\u0941\\u092a\\u093e\\u0924\\u0940 \\u0939\\u094b\\u0924\\u0940 \\u0939\\u0948. \\u0905\\u0917\\u0930 \\u092a\\u094d\\u0930\\u0915\\u094d\\u0930\\u093f\\u092f\\u093e \\u0915\\u0947 \\u092a\\u0939\\u0932\\u0947 \\u092e\\u093f\\u0928\\u091f \\u0915\\u0947 \\u0926\\u094c\\u0930\\u093e\\u0928 20% \\u0926\\u0942\\u0937\\u0915 \\u0915\\u094b \\u0939\\u091f\\u093e\\u092f\\u093e \\u091c\\u093e \\u0938\\u0915\\u0924\\u093e \\u0939\\u0948 \\u0914\\u0930 \\u092a\\u093e\\u0928\\u0940 \\u0915\\u094b \\u0938\\u0941\\u0930\\u0915\\u094d\\u0937\\u093f\\u0924 \\u092c\\u0928\\u093e\\u0928\\u0947 \\u0915\\u0947 \\u0932\\u093f\\u090f 98% \\u0915\\u094b \\u0939\\u091f\\u093e\\u092f\\u093e \\u091c\\u093e\\u0928\\u093e \\u091a\\u093e\\u0939\\u093f\\u090f, \\u0924\\u094b \\u0936\\u0941\\u0926\\u094d\\u0927\\u093f\\u0915\\u0930\\u0923 \\u092a\\u094d\\u0930\\u0915\\u094d\\u0930\\u093f\\u092f\\u093e \\u092e\\u0947\\u0902 \\u0932\\u0917\\u092d\\u0917 \\u0915\\u093f\\u0924\\u0928\\u093e \\u0938\\u092e\\u092f \\u0932\\u0917\\u0947\\u0917\\u093e? ###  A) 2 \\u092e\\u093f\\u0928\\u091f B) 5 \\u092e\\u093f\\u0928\\u091f C) 18 \\u092e\\u093f\\u0928\\u091f D) 20 \\u092e\\u093f\\u0928\\u091f ### MCQ ### \"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Output\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"A\",\n          \"C\",\n          \"B\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sub-Domain\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 57,\n        \"samples\": [\n          \"college_medicine\",\n          \"security_studies\",\n          \"high_school_microeconomics\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Dataset\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"MMLU\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"tok\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 164,\n        \"min\": 29,\n        \"max\": 1917,\n        \"num_unique_values\": 831,\n        \"samples\": [\n          251\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 65
+        }
+      ],
+      "source": [
+        "df.head(10)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 66,
+      "id": "5af6bcac-3c98-421b-8f4b-854b57db8416",
+      "metadata": {
+        "id": "5af6bcac-3c98-421b-8f4b-854b57db8416",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 104
+        },
+        "outputId": "c7870936-d0b2-4d04-da68-55dfae67eb2b"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "'from tqdm import tqdm\\nimport torch\\ndef generate_responses_phi4_batched(df, tokenizer, model, batch_size=8):\\n    responses = []\\n    for i in tqdm(range(0, len(df), batch_size), desc=\"Processing Batches\"):\\n        batch = df[\\'Input\\'][i:i + batch_size].tolist()\\n        prompts = [f\"### INPUT : {text} ### MCQ ### OUTPUT :\" for text in batch]\\n        messages = [{\"role\": \"user\", \"content\": prompt} for prompt in prompts]\\n        inputs = [tokenizer.apply_chat_template([msg], tokenize=True, add_generation_prompt=True, return_tensors=\"pt\") for msg in messages]\\n        max_length = max(input_tensor.size(1) for input_tensor in inputs)\\n        padded_inputs = []\\n        for input_tensor in inputs:\\n            pad_size = max_length - input_tensor.size(1)\\n            padded_tensor = torch.nn.functional.pad(input_tensor, (0, pad_size), value=tokenizer.pad_token_id)\\n            padded_inputs.append(padded_tensor)\\n        batch_inputs = torch.cat(padded_inputs, dim=0).to(\"cuda\")\\n        outputs = model.generate(input_ids=batch_inputs, max_new_tokens=20, use_cache=True, temperature=0.1, min_p=0.1, pad_token_id=tokenizer.eos_token_id)\\n        batch_responses = tokenizer.batch_decode(outputs, skip_special_tokens=True)\\n        for response in batch_responses:\\n            processed_response = response.split(\"### OUTPUT :\\nassistant\")[-1].strip()\\n            responses.append(processed_response)\\n    df[\\'Response\\'] = responses\\n    return df'"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "string"
+            }
+          },
+          "metadata": {},
+          "execution_count": 66
+        }
+      ],
+      "source": [
+        "\"\"\"from tqdm import tqdm\n",
+        "import torch\n",
+        "def generate_responses_phi4_batched(df, tokenizer, model, batch_size=8):\n",
+        "    responses = []\n",
+        "    for i in tqdm(range(0, len(df), batch_size), desc=\"Processing Batches\"):\n",
+        "        batch = df['Input'][i:i + batch_size].tolist()\n",
+        "        prompts = [f\"### INPUT : {text} ### MCQ ### OUTPUT :\" for text in batch]\n",
+        "        messages = [{\"role\": \"user\", \"content\": prompt} for prompt in prompts]\n",
+        "        inputs = [tokenizer.apply_chat_template([msg], tokenize=True, add_generation_prompt=True, return_tensors=\"pt\") for msg in messages]\n",
+        "        max_length = max(input_tensor.size(1) for input_tensor in inputs)\n",
+        "        padded_inputs = []\n",
+        "        for input_tensor in inputs:\n",
+        "            pad_size = max_length - input_tensor.size(1)\n",
+        "            padded_tensor = torch.nn.functional.pad(input_tensor, (0, pad_size), value=tokenizer.pad_token_id)\n",
+        "            padded_inputs.append(padded_tensor)\n",
+        "        batch_inputs = torch.cat(padded_inputs, dim=0).to(\"cuda\")\n",
+        "        outputs = model.generate(input_ids=batch_inputs, max_new_tokens=20, use_cache=True, temperature=0.1, min_p=0.1, pad_token_id=tokenizer.eos_token_id)\n",
+        "        batch_responses = tokenizer.batch_decode(outputs, skip_special_tokens=True)\n",
+        "        for response in batch_responses:\n",
+        "            processed_response = response.split(\"### OUTPUT :\\nassistant\")[-1].strip()\n",
+        "            responses.append(processed_response)\n",
+        "    df['Response'] = responses\n",
+        "    return df\"\"\""
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df[14000:]"
+      ],
+      "metadata": {
+        "id": "DnE5jnbPTd03",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "outputId": "93fbcec5-1269-4a00-bcbf-b59fb49138fc"
+      },
+      "id": "DnE5jnbPTd03",
+      "execution_count": 67,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                                                   Input Output  \\\n",
+              "2399   100 का तीन पांचवा भाग क्या है? ###  A) 3 B) 5 ...      D   \n",
+              "2277   कौन सी संख्या 7 का गुणज है? ###  A) 27 B) 48 C...      C   \n",
+              "7890   तीन स्टूज में से कौन अन्य से संबंधित नहीं था? ...      B   \n",
+              "2274   −8 • (−4) का गुणनफल ज्ञात कीजिए। ###  A) −4 B)...      C   \n",
+              "7667   लौवर संग्रहालय कहां है? ###  A) पेरिस B) ल्योन...      A   \n",
+              "7410   पेरेग्रन किस तरह का जानवर है? ###  A) मूज़  B) ...      C   \n",
+              "669    पानी का pH मान कितना है? ###  A) 3.5 B) 7 C) 1...      B   \n",
+              "3204   Python 3 में, निम्न में से कौन सा फ़्लोर डिवीज...      B   \n",
+              "7421   आप एक युवा गाय को क्या कहते हैं?  ###  A) घोड़...      D   \n",
+              "2107   किस संख्या का निरपेक्ष मान 5 से अधिक है? ###  ...      A   \n",
+              "38     परिमित क्षेत्र Z_7 के लिए जनरेटर पता करें. ###...      C   \n",
+              "7529   आपका हॉलक्स क्या है? ###  A) कान का लोब B) जीभ...      D   \n",
+              "2126   एक दशक में कितने वर्ष होते हैं? ###  A) 5 B) 1...      B   \n",
+              "7722   इनमें से कौन मसाला नहीं है? ###  A) डिल B) सौं...      C   \n",
+              "1552   WPA किस प्रकार के एन्क्रिप्शन का उपयोग करता है...      C   \n",
+              "13949  भक्ति का प्रायः क्या अनुवाद किया जाता है? ### ...      C   \n",
+              "3142   निम्नलिखित में से कौन सा एक रेडियोधर्मी तत्व ह...      C   \n",
+              "2112   Compute 22 / 2 + 9. ###  A) 10 B) 11 C) 20 D) ...      C   \n",
+              "5077   निम्नलिखित में से कौन द्वितीयक प्रबलक है? ### ...      C   \n",
+              "7872   बेसबॉल में कितनी गेंदें वॉक करती हैं? ###  A) ...      D   \n",
+              "7737   इनमें से कौन सी फलियां नहीं हैं? ###  A) फलिया...      C   \n",
+              "2150   8 + 8 ÷ 2 + 2 = ###  A) 4 B) 8 C) 10 D) 14 ###...      D   \n",
+              "3161   निम्नलिखित में से किसे मेटलॉइड माना जाता है? #...      C   \n",
+              "8041   इनमें से कौन सी मिर्च का प्रकार नहीं है? ###  ...      B   \n",
+              "77     वलय Z x Z की विशेषता पता करें. ###  A) 0 B) 3 ...      A   \n",
+              "7744   जिराफ़ की कितनी आँखें होती हैं? ###  A) एक बार...      B   \n",
+              "1766   नीले रंग का पूरक रंग है ###  A) मैजेंटा B) पील...      B   \n",
+              "3899   सरकार इसका उपयोग करके मुद्रास्फीति को मापती है...      C   \n",
+              "7548   सर्वहारा वर्ग क्या है? ###  A) बेघर B) राजपरिव...      D   \n",
+              "7686   अरबी अंक '2' को कैसे लिखा जाता है? ###  A) 2 B...      A   \n",
+              "7971   आइस हॉकी खेल में कितने पीरियड होते हैं? ###  A...      C   \n",
+              "7681   इनमें से कौन सा शब्द सही वर्तनी वाला है? ###  ...      C   \n",
+              "7851   बैकगैमौन कितने खिलाड़ियों का खेल है? ###  A) द...      A   \n",
+              "8138   गेरी एडम्स किस संगठन के अध्यक��ष हैं? ###  A) G...      C   \n",
+              "1190   (1+i)^10 = ###  A) 1 B) i C) 32 D) 32i ### MCQ...      D   \n",
+              "7624   इनमें से कौन सा सामान्यतः ज्ञात निवेश खाता है?...      C   \n",
+              "8005   निम्नलिखित में से कौन सा तत्व धातु है? ###  A)...      D   \n",
+              "2087   −4 +  ( −3 )= ###  A) −7 B) −1 C) 1 D) 7 ### M...      A   \n",
+              "8009   माणिक्य किस रंग का होता है? ###  A) लाल B) काल...      A   \n",
+              "7772   इनमें से कौन सा शब्द क्रिया विशेषण है? ###  A)...      D   \n",
+              "7585   बल = द्रव्यमान = क्या? ###  A) वेग B) दूरी C) ...      C   \n",
+              "2983   एंटीमोनी का प्रतीक … है ###  A) W B) Sb C) Fe ...      B   \n",
+              "\n",
+              "                         Sub-Domain Dataset  tok  \n",
+              "2399         elementary_mathematics    MMLU   38  \n",
+              "2277         elementary_mathematics    MMLU   38  \n",
+              "7890                  miscellaneous    MMLU   38  \n",
+              "2274         elementary_mathematics    MMLU   38  \n",
+              "7667                  miscellaneous    MMLU   38  \n",
+              "7410                  miscellaneous    MMLU   38  \n",
+              "669              clinical_knowledge    MMLU   38  \n",
+              "3204   high_school_computer_science    MMLU   38  \n",
+              "7421                  miscellaneous    MMLU   38  \n",
+              "2107         elementary_mathematics    MMLU   38  \n",
+              "38                 abstract_algebra    MMLU   38  \n",
+              "7529                  miscellaneous    MMLU   38  \n",
+              "2126         elementary_mathematics    MMLU   37  \n",
+              "7722                  miscellaneous    MMLU   37  \n",
+              "1552              computer_security    MMLU   37  \n",
+              "13949               world_religions    MMLU   37  \n",
+              "3142          high_school_chemistry    MMLU   37  \n",
+              "2112         elementary_mathematics    MMLU   37  \n",
+              "5077         high_school_psychology    MMLU   37  \n",
+              "7872                  miscellaneous    MMLU   37  \n",
+              "7737                  miscellaneous    MMLU   37  \n",
+              "2150         elementary_mathematics    MMLU   36  \n",
+              "3161          high_school_chemistry    MMLU   36  \n",
+              "8041                  miscellaneous    MMLU   36  \n",
+              "77                 abstract_algebra    MMLU   36  \n",
+              "7744                  miscellaneous    MMLU   36  \n",
+              "1766             conceptual_physics    MMLU   36  \n",
+              "3899     high_school_macroeconomics    MMLU   35  \n",
+              "7548                  miscellaneous    MMLU   35  \n",
+              "7686                  miscellaneous    MMLU   35  \n",
+              "7971                  miscellaneous    MMLU   35  \n",
+              "7681                  miscellaneous    MMLU   35  \n",
+              "7851                  miscellaneous    MMLU   35  \n",
+              "8138                  miscellaneous    MMLU   35  \n",
+              "1190            college_mathematics    MMLU   33  \n",
+              "7624                  miscellaneous    MMLU   33  \n",
+              "8005                  miscellaneous    MMLU   33  \n",
+              "2087         elementary_mathematics    MMLU   32  \n",
+              "8009                  miscellaneous    MMLU   32  \n",
+              "7772                  miscellaneous    MMLU   31  \n",
+              "7585                  miscellaneous    MMLU   31  \n",
+              "2983          high_school_chemistry    MMLU   29  "
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-2e03fd90-eced-4288-a341-8006fa27daaf\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Input</th>\n",
+              "      <th>Output</th>\n",
+              "      <th>Sub-Domain</th>\n",
+              "      <th>Dataset</th>\n",
+              "      <th>tok</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>2399</th>\n",
+              "      <td>100 का तीन पांचवा भाग क्या है? ###  A) 3 B) 5 ...</td>\n",
+              "      <td>D</td>\n",
+              "      <td>elementary_mathematics</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>38</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2277</th>\n",
+              "      <td>कौन सी संख्या 7 का गुणज है? ###  A) 27 B) 48 C...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>elementary_mathematics</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>38</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7890</th>\n",
+              "      <td>तीन स्टूज में से कौन अन्य से संबंधित नहीं था? ...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>38</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2274</th>\n",
+              "      <td>−8 • (−4) का गुणनफल ज्ञात कीजिए। ###  A) −4 B)...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>elementary_mathematics</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>38</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7667</th>\n",
+              "      <td>लौवर संग्रहालय कहां है? ###  A) पेरिस B) ल्योन...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>38</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7410</th>\n",
+              "      <td>पेरेग्रन किस तरह का जानवर है? ###  A) मूज़  B) ...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>38</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>669</th>\n",
+              "      <td>पानी का pH मान कितना है? ###  A) 3.5 B) 7 C) 1...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>clinical_knowledge</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>38</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3204</th>\n",
+              "      <td>Python 3 में, निम्न में से कौन सा फ़्लोर डिवीज...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>high_school_computer_science</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>38</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7421</th>\n",
+              "      <td>आप एक युवा गाय को क्या कहते हैं?  ###  A) घोड़...</td>\n",
+              "      <td>D</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>38</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2107</th>\n",
+              "      <td>किस संख्या का निरपेक्ष मान 5 से अधिक है? ###  ...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>elementary_mathematics</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>38</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>38</th>\n",
+              "      <td>परिमित क्षेत्र Z_7 के लिए जनरेटर पता करें. ###...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>abstract_algebra</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>38</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7529</th>\n",
+              "      <td>आपका हॉलक्स क्या है? ###  A) कान का लोब B) जीभ...</td>\n",
+              "      <td>D</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>38</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2126</th>\n",
+              "      <td>एक दशक में कितने वर्ष होते हैं? ###  A) 5 B) 1...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>elementary_mathematics</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>37</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7722</th>\n",
+              "      <td>इनमें से कौन मसाला नहीं है? ###  A) डिल B) सौं...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>37</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1552</th>\n",
+              "      <td>WPA किस प्रकार के एन्क्रिप्शन का उपयोग करता है...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>computer_security</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>37</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>13949</th>\n",
+              "      <td>भक्ति का प्रायः क्या अनुवाद किया जाता है? ### ...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>world_religions</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>37</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3142</th>\n",
+              "      <td>निम्नलिखित में से कौन सा एक रेडियोधर्मी तत्व ह...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>high_school_chemistry</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>37</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2112</th>\n",
+              "      <td>Compute 22 / 2 + 9. ###  A) 10 B) 11 C) 20 D) ...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>elementary_mathematics</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>37</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5077</th>\n",
+              "      <td>निम्नलिखित में से कौन द्वितीयक प्रबलक है? ### ...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>high_school_psychology</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>37</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7872</th>\n",
+              "      <td>बेसबॉल में कितनी गेंदें वॉक करती हैं? ###  A) ...</td>\n",
+              "      <td>D</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>37</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7737</th>\n",
+              "      <td>इनमें से कौन सी फलियां नहीं हैं? ###  A) फलिया...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>37</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2150</th>\n",
+              "      <td>8 + 8 ÷ 2 + 2 = ###  A) 4 B) 8 C) 10 D) 14 ###...</td>\n",
+              "      <td>D</td>\n",
+              "      <td>elementary_mathematics</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>36</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3161</th>\n",
+              "      <td>निम्नलिखित में से किसे मेटलॉइड माना जाता है? #...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>high_school_chemistry</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>36</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8041</th>\n",
+              "      <td>इनमें से कौन सी मिर्च का प्रकार नहीं है? ###  ...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>36</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>77</th>\n",
+              "      <td>वलय Z x Z की विशेषता पता करें. ###  A) 0 B) 3 ...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>abstract_algebra</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>36</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7744</th>\n",
+              "      <td>जिराफ़ की कितनी आँखें होती हैं? ###  A) एक बार...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>36</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1766</th>\n",
+              "      <td>नीले रंग का पूरक रंग है ###  A) मैजेंटा B) पील...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>conceptual_physics</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>36</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3899</th>\n",
+              "      <td>सरकार इसका उपयोग करके मुद्रास्फीति को मापती है...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>high_school_macroeconomics</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>35</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7548</th>\n",
+              "      <td>सर्वहारा वर्ग क्या है? ###  A) बेघर B) राजपरिव...</td>\n",
+              "      <td>D</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>35</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7686</th>\n",
+              "      <td>अरबी अंक '2' को कैसे लिखा जाता है? ###  A) 2 B...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>35</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7971</th>\n",
+              "      <td>आइस हॉकी खेल में कितने पीरियड होते हैं? ###  A...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>35</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7681</th>\n",
+              "      <td>इनमें से कौन सा शब्द सही वर्तनी वाला है? ###  ...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>35</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7851</th>\n",
+              "      <td>बैकगैमौन कितने खिलाड़ियों का खेल है? ###  A) द...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>35</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8138</th>\n",
+              "      <td>गेरी एडम्स किस संगठन के अध्यक्ष हैं? ###  A) G...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>35</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1190</th>\n",
+              "      <td>(1+i)^10 = ###  A) 1 B) i C) 32 D) 32i ### MCQ...</td>\n",
+              "      <td>D</td>\n",
+              "      <td>college_mathematics</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>33</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7624</th>\n",
+              "      <td>इनमें से कौन सा सामान्यतः ज्ञात निवेश खाता है?...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>33</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8005</th>\n",
+              "      <td>निम्नलिखित में से कौन सा तत्व धातु है? ###  A)...</td>\n",
+              "      <td>D</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>33</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2087</th>\n",
+              "      <td>−4 +  ( −3 )= ###  A) −7 B) −1 C) 1 D) 7 ### M...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>elementary_mathematics</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>32</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8009</th>\n",
+              "      <td>माणिक्य किस रंग का होता है? ###  A) लाल B) काल...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>32</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7772</th>\n",
+              "      <td>इनमें से कौन सा शब्द क्रिया विशेषण है? ###  A)...</td>\n",
+              "      <td>D</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>31</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7585</th>\n",
+              "      <td>बल = द्रव्यमान = क्या? ###  A) वेग B) दूरी C) ...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>31</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2983</th>\n",
+              "      <td>एंटीमोनी का प्रतीक … है ###  A) W B) Sb C) Fe ...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>high_school_chemistry</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>29</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2e03fd90-eced-4288-a341-8006fa27daaf')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-2e03fd90-eced-4288-a341-8006fa27daaf button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-2e03fd90-eced-4288-a341-8006fa27daaf');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-bf4e554d-c9db-41e6-8b0f-4c49e58612c5\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-bf4e554d-c9db-41e6-8b0f-4c49e58612c5')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-bf4e554d-c9db-41e6-8b0f-4c49e58612c5 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "summary": "{\n  \"name\": \"df[14000:]\",\n  \"rows\": 42,\n  \"fields\": [\n    {\n      \"column\": \"Input\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 42,\n        \"samples\": [\n          \"\\u091c\\u093f\\u0930\\u093e\\u092b\\u093c \\u0915\\u0940 \\u0915\\u093f\\u0924\\u0928\\u0940 \\u0906\\u0901\\u0916\\u0947\\u0902 \\u0939\\u094b\\u0924\\u0940 \\u0939\\u0948\\u0902? ###  A) \\u090f\\u0915 \\u092c\\u093e\\u0930 B) \\u0926\\u094b \\u092c\\u093e\\u0930 C) \\u0924\\u0940\\u0928 \\u092c\\u093e\\u0930 D) \\u091a\\u093e\\u0930 ### MCQ ### \",\n          \"\\u0907\\u0928\\u092e\\u0947\\u0902 \\u0938\\u0947 \\u0915\\u094c\\u0928 \\u092e\\u0938\\u093e\\u0932\\u093e \\u0928\\u0939\\u0940\\u0902 \\u0939\\u0948? ###  A) \\u0921\\u093f\\u0932 B) \\u0938\\u094c\\u0902\\u092b C) \\u0916\\u0940\\u0930\\u093e D) \\u0915\\u0947\\u092f\\u0947\\u0928 ### MCQ ### \",\n          \"\\u0906\\u092a \\u090f\\u0915 \\u092f\\u0941\\u0935\\u093e \\u0917\\u093e\\u092f \\u0915\\u094b \\u0915\\u094d\\u092f\\u093e \\u0915\\u0939\\u0924\\u0947 \\u0939\\u0948\\u0902?  ###  A) \\u0918\\u094b\\u0921\\u093c\\u0940 B) \\u092d\\u0947\\u0921\\u093c C) \\u092c\\u091a\\u094d\\u091a\\u093e D) \\u092c\\u091b\\u0921\\u093c\\u093e ### MCQ ### \"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Output\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"C\",\n          \"A\",\n          \"D\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sub-Domain\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 12,\n        \"samples\": [\n          \"high_school_macroeconomics\",\n          \"conceptual_physics\",\n          \"elementary_mathematics\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Dataset\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"MMLU\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"tok\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 29,\n        \"max\": 38,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          37\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 67
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import torch\n",
+        "import torch.nn.functional as F\n",
+        "from transformers import AutoTokenizer, AutoModelForCausalLM\n",
+        "input_text = \"जोड़ें 46,911 + 653,092 ### A) 699,903 B) 700,003 C) 913,203 D) 1,122,202 ### MCQ ###\tRespond with just one letter based on these options : \"\n",
+        "prompt = f\"### INPUT : {input_text} RESPONSE : \"\n",
+        "message = [{\"role\": \"user\", \"content\": prompt}]\n",
+        "inputs = tokenizer.apply_chat_template(message, tokenize=True, add_generation_prompt=True, return_tensors=\"pt\").to(\"cuda\")\n",
+        "with torch.no_grad():\n",
+        "    outputs = model.generate(input_ids=inputs, max_new_tokens=1, use_cache=True, pad_token_id=tokenizer.eos_token_id, return_dict_in_generate=True, output_scores=True)\n",
+        "    next_token_logits = outputs.scores[0]\n",
+        "probs = F.softmax(next_token_logits, dim=-1)\n",
+        "token_ids_a = tokenizer.encode('A', add_special_tokens=False)[0]\n",
+        "token_ids_b = tokenizer.encode('B', add_special_tokens=False)[0]\n",
+        "token_ids_c = tokenizer.encode('C', add_special_tokens=False)[0]\n",
+        "token_ids_d = tokenizer.encode('D', add_special_tokens=False)[0]\n",
+        "prob_a = probs[0, token_ids_a].item()\n",
+        "prob_b = probs[0, token_ids_b].item()\n",
+        "prob_c = probs[0, token_ids_c].item()\n",
+        "prob_d = probs[0, token_ids_d].item()\n",
+        "print(f\"Probability of 'A': {prob_a:.4f}\")\n",
+        "print(f\"Probability of 'B': {prob_b:.4f}\")\n",
+        "print(f\"Probability of 'C': {prob_c:.4f}\")\n",
+        "print(f\"Probability of 'D': {prob_d:.4f}\")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "x9Gu8g6zZy_Q",
+        "outputId": "34e3da1a-ac7d-4958-d0fd-f1a0b8b6748a"
+      },
+      "id": "x9Gu8g6zZy_Q",
+      "execution_count": 68,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Probability of 'A': 0.2249\n",
+            "Probability of 'B': 0.3273\n",
+            "Probability of 'C': 0.1204\n",
+            "Probability of 'D': 0.0569\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import torch\n",
+        "import torch.nn.functional as F\n",
+        "from transformers import AutoTokenizer, AutoModelForCausalLM\n",
+        "input_text = \"दिए गए बहुपद के संकेतित परिमित क्षेत्र में गुणांकों के साथ सभी शून्य बताएं. x^5 + 3x^3 + x^2 + 2x in Z_5 ### A) 0 B) 1 C) 0,1 D) 0,4\t### MCQ ### Respond with just one letter based on these options : \"\n",
+        "prompt = f\"### INPUT : {input_text} RESPONSE : \"\n",
+        "message = [{\"role\": \"user\", \"content\": prompt}]\n",
+        "inputs = tokenizer.apply_chat_template(message, tokenize=True, add_generation_prompt=True, return_tensors=\"pt\").to(\"cuda\")\n",
+        "outputs = model.generate(input_ids=inputs, max_new_tokens=200, use_cache=True, temperature=0.1, min_p=0.1, pad_token_id=tokenizer.eos_token_id)\n",
+        "response = tokenizer.decode(outputs[0], skip_special_tokens=True)\n",
+        "processed_response = response.split(\"### RESPONSE :\\nmodel\")[-1].strip()\n",
+        "print(f\"Generated Response (20 tokens):\\n{processed_response}\\n\")\n",
+        "with torch.no_grad():\n",
+        "    outputs = model.generate(input_ids=inputs, max_new_tokens=1, use_cache=True, pad_token_id=tokenizer.eos_token_id, return_dict_in_generate=True, output_scores=True)\n",
+        "    next_token_logits = outputs.scores[0]\n",
+        "probs = F.softmax(next_token_logits, dim=-1)\n",
+        "token_ids_a = tokenizer.encode('A', add_special_tokens=False)[0]\n",
+        "token_ids_b = tokenizer.encode('B', add_special_tokens=False)[0]\n",
+        "token_ids_c = tokenizer.encode('C', add_special_tokens=False)[0]\n",
+        "token_ids_d = tokenizer.encode('D', add_special_tokens=False)[0]\n",
+        "prob_a = probs[0, token_ids_a].item()\n",
+        "prob_b = probs[0, token_ids_b].item()\n",
+        "prob_c = probs[0, token_ids_c].item()\n",
+        "prob_d = probs[0, token_ids_d].item()\n",
+        "print(f\"Probability of 'A': {prob_a:.4f}\")\n",
+        "print(f\"Probability of 'B': {prob_b:.4f}\")\n",
+        "print(f\"Probability of 'C': {prob_c:.4f}\")\n",
+        "print(f\"Probability of 'D': {prob_d:.4f}\")"
+      ],
+      "metadata": {
+        "id": "QuuDF-qci19H",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "4f1285d3-99fd-4ddd-f5de-0e120f3daead"
+      },
+      "id": "QuuDF-qci19H",
+      "execution_count": 69,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Generated Response (20 tokens):\n",
+            "user\n",
+            "### INPUT : दिए गए बहुपद के संकेतित परिमित क्षेत्र में गुणांकों के साथ सभी शून्य बताएं. x^5 + 3x^3 + x^2 + 2x in Z_5 ### A) 0 B) 1 C) 0,1 D) 0,4\t### MCQ ### Respond with just one letter based on these options :  RESPONSE :\n",
+            "model\n",
+            "The correct answer is C. Here's why:\n",
+            "\n",
+            "**Understanding the problem:**\n",
+            "\n",
+            "We are given a polynomial with coefficients in the finite field Z_5 (the integers modulo 5). We need to find all the roots (or zeros) of this polynomial within Z_5.\n",
+            "\n",
+            "**Solving the problem:**\n",
+            "\n",
+            "1. **Substitute values:** Since we are working in Z_5, we only need to check the values 0, 1, 2, 3, and 4 for the roots.\n",
+            "\n",
+            "2. **Check each value:**\n",
+            "   * For x = 0: 0^5 + 3(0)^3 + 0^2 + 2(0) = 0. So, x = 0 is a root.\n",
+            "   * For x = 1: 1^5 + 3(1)^3 + 1^2 + 2(1) = 1 + 3 + 1 +\n",
+            "\n",
+            "Probability of 'A': 0.0456\n",
+            "Probability of 'B': 0.0585\n",
+            "Probability of 'C': 0.0851\n",
+            "Probability of 'D': 0.0965\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import torch\n",
+        "import torch.nn.functional as F\n",
+        "input_text = \"जोड़ें 46,911 + 653,092 ### A) 699,903 B) 700,003 C) 913,203 D) 1,122,202 ### MCQ ###\"\n",
+        "prompt = f\"### INPUT : {input_text} RESPONSE : \"\n",
+        "message = [{\"role\": \"user\", \"content\": prompt}]\n",
+        "inputs = tokenizer.apply_chat_template(message, tokenize=True, add_generation_prompt=True, return_tensors=\"pt\").to(\"cuda\")\n",
+        "outputs = model.generate(input_ids=inputs, max_new_tokens=200, use_cache=True, temperature=0.1, min_p=0.1, pad_token_id=tokenizer.eos_token_id)\n",
+        "response = tokenizer.decode(outputs[0], skip_special_tokens=True)\n",
+        "processed_response = response.split(\"### RESPONSE :\\nmodel\")[-1].strip()\n",
+        "print(f\"Generated Response (20 tokens):\\n{processed_response}\\n\")\n",
+        "with torch.no_grad():\n",
+        "    outputs = model.generate(input_ids=inputs, max_new_tokens=3, use_cache=True, pad_token_id=tokenizer.eos_token_id, return_dict_in_generate=True, output_scores=True)\n",
+        "    scores = outputs.scores\n",
+        "token_ids_a = tokenizer.encode('A', add_special_tokens=False)[0]\n",
+        "token_ids_b = tokenizer.encode('B', add_special_tokens=False)[0]\n",
+        "token_ids_c = tokenizer.encode('C', add_special_tokens=False)[0]\n",
+        "token_ids_d = tokenizer.encode('D', add_special_tokens=False)[0]\n",
+        "for i, score in enumerate(scores, 1):\n",
+        "    probs = F.softmax(score, dim=-1)\n",
+        "    prob_a = probs[0, token_ids_a].item()\n",
+        "    prob_b = probs[0, token_ids_b].item()\n",
+        "    prob_c = probs[0, token_ids_c].item()\n",
+        "    prob_d = probs[0, token_ids_d].item()\n",
+        "    print(f\"Probability of 'A' at token {i}: {prob_a:.4f}\")\n",
+        "    print(f\"Probability of 'B' at token {i}: {prob_b:.4f}\")\n",
+        "    print(f\"Probability of 'C' at token {i}: {prob_c:.4f}\")\n",
+        "    print(f\"Probability of 'D' at token {i}: {prob_d:.4f}\")"
+      ],
+      "metadata": {
+        "id": "r1dozae-gO5B",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "06fc9e40-58d5-4915-d48f-f57fd2a8ecf1"
+      },
+      "id": "r1dozae-gO5B",
+      "execution_count": 70,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Generated Response (20 tokens):\n",
+            "The correct answer is B) 700,003. \n",
+            "\n",
+            "Here's how to add the numbers:\n",
+            "\n",
+            "46,911\n",
+            "+ 653,092\n",
+            "----------\n",
+            "700,003\n",
+            "\n",
+            "Probability of 'A' at token 1: 0.0057\n",
+            "Probability of 'B' at token 1: 0.0021\n",
+            "Probability of 'C' at token 1: 0.0009\n",
+            "Probability of 'D' at token 1: 0.0014\n",
+            "Probability of 'A' at token 2: 0.0000\n",
+            "Probability of 'B' at token 2: 0.0000\n",
+            "Probability of 'C' at token 2: 0.0000\n",
+            "Probability of 'D' at token 2: 0.0000\n",
+            "Probability of 'A' at token 3: 0.0000\n",
+            "Probability of 'B' at token 3: 0.0000\n",
+            "Probability of 'C' at token 3: 0.0000\n",
+            "Probability of 'D' at token 3: 0.0000\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import torch\n",
+        "import torch.nn.functional as F\n",
+        "from transformers import AutoTokenizer, AutoModelForCausalLM\n",
+        "from tqdm import tqdm\n",
+        "responses = []\n",
+        "prob_a1_list = []\n",
+        "prob_a2_list = []\n",
+        "prob_a3_list = []\n",
+        "prob_b1_list = []\n",
+        "prob_b2_list = []\n",
+        "prob_b3_list = []\n",
+        "prob_c1_list = []\n",
+        "prob_c2_list = []\n",
+        "prob_c3_list = []\n",
+        "prob_d1_list = []\n",
+        "prob_d2_list = []\n",
+        "prob_d3_list = []\n",
+        "batch_size = 1\n",
+        "for start in tqdm(range(0, len(df), batch_size)):\n",
+        "    batch_texts = df['Input'][start:start+batch_size].tolist()\n",
+        "    for input_text in batch_texts:\n",
+        "        prompt = f\"### INPUT : {input_text} Respond with just one letter based on these options : \"\n",
+        "        message = [{\"role\": \"user\", \"content\": prompt}]\n",
+        "        inputs = tokenizer.apply_chat_template(message, tokenize=True, add_generation_prompt=True, return_tensors=\"pt\").to(\"cuda\")\n",
+        "        with torch.no_grad():\n",
+        "            outputs = model.generate(input_ids=inputs, max_new_tokens=3, use_cache=True, pad_token_id=tokenizer.eos_token_id, return_dict_in_generate=True, output_scores=True)\n",
+        "            scores = outputs.scores  # tuple of [batch_size, vocab_size] for each token\n",
+        "        token_ids_a = tokenizer.encode('A', add_special_tokens=False)[0]\n",
+        "        token_ids_b = tokenizer.encode('B', add_special_tokens=False)[0]\n",
+        "        token_ids_c = tokenizer.encode('C', add_special_tokens=False)[0]\n",
+        "        token_ids_d = tokenizer.encode('D', add_special_tokens=False)[0]\n",
+        "        for i in range(3):\n",
+        "            if i < len(scores):\n",
+        "                probs = F.softmax(scores[i], dim=-1)\n",
+        "                prob_a = probs[0, token_ids_a].item()\n",
+        "                prob_b = probs[0, token_ids_b].item()\n",
+        "                prob_c = probs[0, token_ids_c].item()\n",
+        "                prob_d = probs[0, token_ids_d].item()\n",
+        "            else:\n",
+        "                prob_a, prob_b, prob_c, prob_d = 0.0, 0.0, 0.0, 0.0\n",
+        "            if i == 0:\n",
+        "                prob_a1_list.append(prob_a)\n",
+        "                prob_b1_list.append(prob_b)\n",
+        "                prob_c1_list.append(prob_c)\n",
+        "                prob_d1_list.append(prob_d)\n",
+        "            elif i == 1:\n",
+        "                prob_a2_list.append(prob_a)\n",
+        "                prob_b2_list.append(prob_b)\n",
+        "                prob_c2_list.append(prob_c)\n",
+        "                prob_d2_list.append(prob_d)\n",
+        "            elif i == 2:\n",
+        "                prob_a3_list.append(prob_a)\n",
+        "                prob_b3_list.append(prob_b)\n",
+        "                prob_c3_list.append(prob_c)\n",
+        "                prob_d3_list.append(prob_d)\n",
+        "df['A1'] = prob_a1_list\n",
+        "df['A2'] = prob_a2_list\n",
+        "df['A3'] = prob_a3_list\n",
+        "df['B1'] = prob_b1_list\n",
+        "df['B2'] = prob_b2_list\n",
+        "df['B3'] = prob_b3_list\n",
+        "df['C1'] = prob_c1_list\n",
+        "df['C2'] = prob_c2_list\n",
+        "df['C3'] = prob_c3_list\n",
+        "df['D1'] = prob_d1_list\n",
+        "df['D2'] = prob_d2_list\n",
+        "df['D3'] = prob_d3_list"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "uyYEgG7_khiV",
+        "outputId": "51457caf-4f4d-4fa4-f0da-f044fc52a2fa"
+      },
+      "id": "uyYEgG7_khiV",
+      "execution_count": 71,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "100%|██████████| 14042/14042 [53:27<00:00,  4.38it/s]\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "\"\"\"import torch\n",
+        "import torch.nn.functional as F\n",
+        "from transformers import AutoTokenizer, AutoModelForCausalLM\n",
+        "responses = []\n",
+        "prob_a_list = []\n",
+        "prob_b_list = []\n",
+        "prob_c_list = []\n",
+        "prob_d_list = []\n",
+        "batch_size = 1\n",
+        "for start in tqdm(range(0, len(df), batch_size)):\n",
+        "    batch_texts = df['Input'][start:start+batch_size].tolist()\n",
+        "    for input_text in batch_texts:\n",
+        "        prompt = f\"### INPUT : {input_text} Respond with just one letter based on these options : \"\n",
+        "        message = [{\"role\": \"user\", \"content\": prompt}]\n",
+        "        inputs = tokenizer.apply_chat_template(message, tokenize=True, add_generation_prompt=True, return_tensors=\"pt\").to(\"cuda\")\n",
+        "        with torch.no_grad():\n",
+        "            outputs = model.generate(input_ids=inputs, max_new_tokens=1, use_cache=True, pad_token_id=tokenizer.eos_token_id, return_dict_in_generate=True, output_scores=True)\n",
+        "            next_token_logits = outputs.scores[0]\n",
+        "        probs = F.softmax(next_token_logits, dim=-1)\n",
+        "        token_ids_a = tokenizer.encode('A', add_special_tokens=False)[0]\n",
+        "        token_ids_b = tokenizer.encode('B', add_special_tokens=False)[0]\n",
+        "        token_ids_c = tokenizer.encode('C', add_special_tokens=False)[0]\n",
+        "        token_ids_d = tokenizer.encode('D', add_special_tokens=False)[0]\n",
+        "        prob_a_list.append(probs[0, token_ids_a].item())\n",
+        "        prob_b_list.append(probs[0, token_ids_b].item())\n",
+        "        prob_c_list.append(probs[0, token_ids_c].item())\n",
+        "        prob_d_list.append(probs[0, token_ids_d].item())\n",
+        "df['A'] = prob_a_list\n",
+        "df['B'] = prob_b_list\n",
+        "df['C'] = prob_c_list\n",
+        "df['D'] = prob_d_list\"\"\""
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 104
+        },
+        "id": "WFl4ieGwkF0G",
+        "outputId": "a21fab31-f1a0-4e85-fe38-bc4452c26023"
+      },
+      "id": "WFl4ieGwkF0G",
+      "execution_count": 72,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "'import torch\\nimport torch.nn.functional as F\\nfrom transformers import AutoTokenizer, AutoModelForCausalLM\\nresponses = []\\nprob_a_list = []\\nprob_b_list = []\\nprob_c_list = []\\nprob_d_list = []\\nbatch_size = 1\\nfor start in tqdm(range(0, len(df), batch_size)):\\n    batch_texts = df[\\'Input\\'][start:start+batch_size].tolist()\\n    for input_text in batch_texts:\\n        prompt = f\"### INPUT : {input_text} Respond with just one letter based on these options : \"\\n        message = [{\"role\": \"user\", \"content\": prompt}]\\n        inputs = tokenizer.apply_chat_template(message, tokenize=True, add_generation_prompt=True, return_tensors=\"pt\").to(\"cuda\")\\n        with torch.no_grad():\\n            outputs = model.generate(input_ids=inputs, max_new_tokens=1, use_cache=True, pad_token_id=tokenizer.eos_token_id, return_dict_in_generate=True, output_scores=True)\\n            next_token_logits = outputs.scores[0]\\n        probs = F.softmax(next_token_logits, dim=-1)\\n        token_ids_a = tokenizer.encode(\\'A\\', add_special_tokens=False)[0]\\n        token_ids_b = tokenizer.encode(\\'B\\', add_special_tokens=False)[0]\\n        token_ids_c = tokenizer.encode(\\'C\\', add_special_tokens=False)[0]\\n        token_ids_d = tokenizer.encode(\\'D\\', add_special_tokens=False)[0]\\n        prob_a_list.append(probs[0, token_ids_a].item())\\n        prob_b_list.append(probs[0, token_ids_b].item())\\n        prob_c_list.append(probs[0, token_ids_c].item())\\n        prob_d_list.append(probs[0, token_ids_d].item())\\ndf[\\'A\\'] = prob_a_list\\ndf[\\'B\\'] = prob_b_list\\ndf[\\'C\\'] = prob_c_list\\ndf[\\'D\\'] = prob_d_list'"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "string"
+            }
+          },
+          "metadata": {},
+          "execution_count": 72
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 423
+        },
+        "id": "y9FMYJ1s2BZG",
+        "outputId": "a851d1e7-8dda-4f6f-8cb2-1f77d7387ea7"
+      },
+      "id": "y9FMYJ1s2BZG",
+      "execution_count": 73,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                                                  Input Output  \\\n",
+              "1262  सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...      B   \n",
+              "1202  सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...      A   \n",
+              "1289  सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...      A   \n",
+              "1246  सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...      D   \n",
+              "1358  सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...      D   \n",
+              "...                                                 ...    ...   \n",
+              "2087  −4 +  ( −3 )= ###  A) −7 B) −1 C) 1 D) 7 ### M...      A   \n",
+              "8009  माणिक्य किस रंग का होता है? ###  A) लाल B) काल...      A   \n",
+              "7772  इनमें से कौन सा शब्द क्रिया विशेषण है? ###  A)...      D   \n",
+              "7585  बल = द्रव्यमान = क्या? ###  A) वेग B) दूरी C) ...      C   \n",
+              "2983  एंटीमोनी का प्रतीक … है ###  A) W B) Sb C) Fe ...      B   \n",
+              "\n",
+              "                  Sub-Domain Dataset   tok        A1            A2   A3  \\\n",
+              "1262        college_medicine    MMLU  1917  0.516257  3.852689e-07  0.0   \n",
+              "1202        college_medicine    MMLU  1894  0.954477  2.689888e-07  0.0   \n",
+              "1289        college_medicine    MMLU  1892  0.424950  2.352290e-07  0.0   \n",
+              "1246        college_medicine    MMLU  1831  0.225298  1.737284e-07  0.0   \n",
+              "1358        college_medicine    MMLU  1830  0.021581  6.391137e-08  0.0   \n",
+              "...                      ...     ...   ...       ...           ...  ...   \n",
+              "2087  elementary_mathematics    MMLU    32  0.905976  5.020378e-07  0.0   \n",
+              "8009           miscellaneous    MMLU    32  0.967982  1.368823e-06  0.0   \n",
+              "7772           miscellaneous    MMLU    31  0.071688  1.060347e-06  0.0   \n",
+              "7585           miscellaneous    MMLU    31  0.090459  3.241587e-07  0.0   \n",
+              "2983   high_school_chemistry    MMLU    29  0.027733  6.366120e-07  0.0   \n",
+              "\n",
+              "            B1            B2   B3        C1            C2   C3        D1  \\\n",
+              "1262  0.354818  3.030374e-06  0.0  0.048019  2.790878e-08  0.0  0.069868   \n",
+              "1202  0.025436  2.689888e-07  0.0  0.012015  2.835121e-08  0.0  0.003442   \n",
+              "1289  0.121750  1.271636e-06  0.0  0.021157  5.947521e-08  0.0  0.424950   \n",
+              "1246  0.693966  3.455002e-07  0.0  0.030491  1.737284e-07  0.0  0.039151   \n",
+              "1358  0.917626  2.836049e-08  0.0  0.021581  1.831091e-08  0.0  0.031399   \n",
+              "...        ...           ...  ...       ...           ...  ...       ...   \n",
+              "2087  0.045106  2.249978e-06  0.0  0.018803  4.970848e-08  0.0  0.012923   \n",
+              "8009  0.013808  9.407772e-07  0.0  0.007391  8.750592e-08  0.0  0.004483   \n",
+              "7772  0.023274  1.527574e-07  0.0  0.018126  4.111410e-08  0.0  0.873344   \n",
+              "7585  0.022872  5.344473e-07  0.0  0.858254  8.196014e-08  0.0  0.017812   \n",
+              "2983  0.918378  1.625646e-06  0.0  0.004819  2.824948e-07  0.0  0.004819   \n",
+              "\n",
+              "                D2   D3  \n",
+              "1262  2.621788e-08  0.0  \n",
+              "1202  2.053755e-09  0.0  \n",
+              "1289  2.639196e-08  0.0  \n",
+              "1246  1.339650e-08  0.0  \n",
+              "1358  2.054427e-09  0.0  \n",
+              "...            ...  ...  \n",
+              "2087  2.499499e-08  0.0  \n",
+              "8009  3.219163e-08  0.0  \n",
+              "7772  1.189676e-07  0.0  \n",
+              "7585  1.192513e-07  0.0  \n",
+              "2983  7.603246e-08  0.0  \n",
+              "\n",
+              "[14042 rows x 17 columns]"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-972b0257-e8b7-4acf-b386-acb40e81e756\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Input</th>\n",
+              "      <th>Output</th>\n",
+              "      <th>Sub-Domain</th>\n",
+              "      <th>Dataset</th>\n",
+              "      <th>tok</th>\n",
+              "      <th>A1</th>\n",
+              "      <th>A2</th>\n",
+              "      <th>A3</th>\n",
+              "      <th>B1</th>\n",
+              "      <th>B2</th>\n",
+              "      <th>B3</th>\n",
+              "      <th>C1</th>\n",
+              "      <th>C2</th>\n",
+              "      <th>C3</th>\n",
+              "      <th>D1</th>\n",
+              "      <th>D2</th>\n",
+              "      <th>D3</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>1262</th>\n",
+              "      <td>सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>college_medicine</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1917</td>\n",
+              "      <td>0.516257</td>\n",
+              "      <td>3.852689e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.354818</td>\n",
+              "      <td>3.030374e-06</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.048019</td>\n",
+              "      <td>2.790878e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.069868</td>\n",
+              "      <td>2.621788e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1202</th>\n",
+              "      <td>सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>college_medicine</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1894</td>\n",
+              "      <td>0.954477</td>\n",
+              "      <td>2.689888e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.025436</td>\n",
+              "      <td>2.689888e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.012015</td>\n",
+              "      <td>2.835121e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.003442</td>\n",
+              "      <td>2.053755e-09</td>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1289</th>\n",
+              "      <td>सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>college_medicine</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1892</td>\n",
+              "      <td>0.424950</td>\n",
+              "      <td>2.352290e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.121750</td>\n",
+              "      <td>1.271636e-06</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.021157</td>\n",
+              "      <td>5.947521e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.424950</td>\n",
+              "      <td>2.639196e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1246</th>\n",
+              "      <td>सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...</td>\n",
+              "      <td>D</td>\n",
+              "      <td>college_medicine</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1831</td>\n",
+              "      <td>0.225298</td>\n",
+              "      <td>1.737284e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.693966</td>\n",
+              "      <td>3.455002e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.030491</td>\n",
+              "      <td>1.737284e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.039151</td>\n",
+              "      <td>1.339650e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1358</th>\n",
+              "      <td>सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...</td>\n",
+              "      <td>D</td>\n",
+              "      <td>college_medicine</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1830</td>\n",
+              "      <td>0.021581</td>\n",
+              "      <td>6.391137e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.917626</td>\n",
+              "      <td>2.836049e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.021581</td>\n",
+              "      <td>1.831091e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.031399</td>\n",
+              "      <td>2.054427e-09</td>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2087</th>\n",
+              "      <td>−4 +  ( −3 )= ###  A) −7 B) −1 C) 1 D) 7 ### M...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>elementary_mathematics</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>32</td>\n",
+              "      <td>0.905976</td>\n",
+              "      <td>5.020378e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.045106</td>\n",
+              "      <td>2.249978e-06</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.018803</td>\n",
+              "      <td>4.970848e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.012923</td>\n",
+              "      <td>2.499499e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>8009</th>\n",
+              "      <td>माणिक्य किस रंग का होता है? ###  A) लाल B) काल...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>32</td>\n",
+              "      <td>0.967982</td>\n",
+              "      <td>1.368823e-06</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.013808</td>\n",
+              "      <td>9.407772e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.007391</td>\n",
+              "      <td>8.750592e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.004483</td>\n",
+              "      <td>3.219163e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7772</th>\n",
+              "      <td>इनमें से कौन सा शब्द क्रिया विशेषण है? ###  A)...</td>\n",
+              "      <td>D</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>31</td>\n",
+              "      <td>0.071688</td>\n",
+              "      <td>1.060347e-06</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.023274</td>\n",
+              "      <td>1.527574e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.018126</td>\n",
+              "      <td>4.111410e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.873344</td>\n",
+              "      <td>1.189676e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>7585</th>\n",
+              "      <td>बल = द्रव्यमान = क्या? ###  A) वेग B) दूरी C) ...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>miscellaneous</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>31</td>\n",
+              "      <td>0.090459</td>\n",
+              "      <td>3.241587e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.022872</td>\n",
+              "      <td>5.344473e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.858254</td>\n",
+              "      <td>8.196014e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.017812</td>\n",
+              "      <td>1.192513e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2983</th>\n",
+              "      <td>एंटीमोनी का प्रतीक … है ###  A) W B) Sb C) Fe ...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>high_school_chemistry</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>29</td>\n",
+              "      <td>0.027733</td>\n",
+              "      <td>6.366120e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.918378</td>\n",
+              "      <td>1.625646e-06</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.004819</td>\n",
+              "      <td>2.824948e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.004819</td>\n",
+              "      <td>7.603246e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>14042 rows × 17 columns</p>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-972b0257-e8b7-4acf-b386-acb40e81e756')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-972b0257-e8b7-4acf-b386-acb40e81e756 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-972b0257-e8b7-4acf-b386-acb40e81e756');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-4bb3f99f-eccf-40d8-82e7-e7acd5738648\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-4bb3f99f-eccf-40d8-82e7-e7acd5738648')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-4bb3f99f-eccf-40d8-82e7-e7acd5738648 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "\n",
+              "  <div id=\"id_e3a25fc6-d2a0-460d-b49b-9a8601a79f5b\">\n",
+              "    <style>\n",
+              "      .colab-df-generate {\n",
+              "        background-color: #E8F0FE;\n",
+              "        border: none;\n",
+              "        border-radius: 50%;\n",
+              "        cursor: pointer;\n",
+              "        display: none;\n",
+              "        fill: #1967D2;\n",
+              "        height: 32px;\n",
+              "        padding: 0 0 0 0;\n",
+              "        width: 32px;\n",
+              "      }\n",
+              "\n",
+              "      .colab-df-generate:hover {\n",
+              "        background-color: #E2EBFA;\n",
+              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "        fill: #174EA6;\n",
+              "      }\n",
+              "\n",
+              "      [theme=dark] .colab-df-generate {\n",
+              "        background-color: #3B4455;\n",
+              "        fill: #D2E3FC;\n",
+              "      }\n",
+              "\n",
+              "      [theme=dark] .colab-df-generate:hover {\n",
+              "        background-color: #434B5C;\n",
+              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "        fill: #FFFFFF;\n",
+              "      }\n",
+              "    </style>\n",
+              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
+              "            title=\"Generate code using this dataframe.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "    <script>\n",
+              "      (() => {\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#id_e3a25fc6-d2a0-460d-b49b-9a8601a79f5b button.colab-df-generate');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      buttonEl.onclick = () => {\n",
+              "        google.colab.notebook.generateWithVariable('df');\n",
+              "      }\n",
+              "      })();\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "variable_name": "df",
+              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 14042,\n  \"fields\": [\n    {\n      \"column\": \"Input\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 13981,\n        \"samples\": [\n          \"\\u0928\\u093f\\u092e\\u094d\\u0928\\u0932\\u093f\\u0916\\u093f\\u0924 \\u092e\\u0947\\u0902 \\u0938\\u0947 \\u0915\\u093f\\u0938 \\u092a\\u0926\\u093e\\u0930\\u094d\\u0925 \\u0915\\u0940 \\u0906\\u0923\\u094d\\u0935\\u093f\\u0915 \\u0938\\u0902\\u0930\\u091a\\u0928\\u093e \\u0905\\u0938\\u092e\\u092e\\u093f\\u0924 \\u0939\\u094b\\u0924\\u0940 \\u0939\\u0948? ###  A) SF4 B) PCl5 C) BF3 D) CO2 ### MCQ ### \",\n          \"\\u090f\\u0915\\u094d\\u0935\\u093f\\u0928\\u093e\\u0938 \\u0915\\u093e \\u0928\\u0948\\u0924\\u093f\\u0915 \\u0938\\u093f\\u0926\\u094d\\u0927\\u093e\\u0902\\u0924 \\u092a\\u094d\\u0930\\u093e\\u0915\\u0943\\u0924\\u093f\\u0915 \\u0915\\u093e\\u0928\\u0942\\u0928 \\u0938\\u093f\\u0926\\u094d\\u0927\\u093e\\u0902\\u0924  ###  A) \\u092a\\u0930\\u093f\\u0923\\u093e\\u092e\\u0935\\u093e\\u0926\\u0964 B) \\u0915\\u093e \\u090f\\u0915 \\u0938\\u0902\\u0938\\u094d\\u0915\\u0930\\u0923 \\u0939\\u0948\\u0964 C) \\u0905\\u0927\\u093f\\u0915\\u093e\\u0930-\\u0906\\u0927\\u093e\\u0930\\u093f\\u0924 \\u0938\\u093f\\u0926\\u094d\\u0927\\u093e\\u0902\\u0924. D) \\u092a\\u0941\\u0923\\u094d\\u092f \\u0928\\u0948\\u0924\\u093f\\u0915\\u0924\\u093e\\u0964 ### MCQ ### \",\n          \"\\u091c\\u093f\\u0938 \\u0926\\u0930 \\u092a\\u0930 \\u0936\\u0941\\u0926\\u094d\\u0927\\u093f\\u0915\\u0930\\u0923 \\u092a\\u094d\\u0930\\u0915\\u094d\\u0930\\u093f\\u092f\\u093e \\u092a\\u093e\\u0928\\u0940 \\u0915\\u0947 \\u091f\\u0948\\u0902\\u0915 \\u0938\\u0947 \\u0926\\u0942\\u0937\\u093f\\u0924 \\u092a\\u0926\\u093e\\u0930\\u094d\\u0925\\u094b\\u0902 \\u0915\\u094b \\u0939\\u091f\\u093e \\u0938\\u0915\\u0924\\u0940 \\u0939\\u0948, \\u0935\\u0939 \\u0936\\u0947\\u0937 \\u0926\\u0942\\u0937\\u093f\\u0924 \\u092a\\u0926\\u093e\\u0930\\u094d\\u0925\\u094b\\u0902 \\u0915\\u0940 \\u092e\\u093e\\u0924\\u094d\\u0930\\u093e \\u0915\\u0947 \\u0938\\u092e\\u093e\\u0928\\u0941\\u092a\\u093e\\u0924\\u0940 \\u0939\\u094b\\u0924\\u0940 \\u0939\\u0948. \\u0905\\u0917\\u0930 \\u092a\\u094d\\u0930\\u0915\\u094d\\u0930\\u093f\\u092f\\u093e \\u0915\\u0947 \\u092a\\u0939\\u0932\\u0947 \\u092e\\u093f\\u0928\\u091f \\u0915\\u0947 \\u0926\\u094c\\u0930\\u093e\\u0928 20% \\u0926\\u0942\\u0937\\u0915 \\u0915\\u094b \\u0939\\u091f\\u093e\\u092f\\u093e \\u091c\\u093e \\u0938\\u0915\\u0924\\u093e \\u0939\\u0948 \\u0914\\u0930 \\u092a\\u093e\\u0928\\u0940 \\u0915\\u094b \\u0938\\u0941\\u0930\\u0915\\u094d\\u0937\\u093f\\u0924 \\u092c\\u0928\\u093e\\u0928\\u0947 \\u0915\\u0947 \\u0932\\u093f\\u090f 98% \\u0915\\u094b \\u0939\\u091f\\u093e\\u092f\\u093e \\u091c\\u093e\\u0928\\u093e \\u091a\\u093e\\u0939\\u093f\\u090f, \\u0924\\u094b \\u0936\\u0941\\u0926\\u094d\\u0927\\u093f\\u0915\\u0930\\u0923 \\u092a\\u094d\\u0930\\u0915\\u094d\\u0930\\u093f\\u092f\\u093e \\u092e\\u0947\\u0902 \\u0932\\u0917\\u092d\\u0917 \\u0915\\u093f\\u0924\\u0928\\u093e \\u0938\\u092e\\u092f \\u0932\\u0917\\u0947\\u0917\\u093e? ###  A) 2 \\u092e\\u093f\\u0928\\u091f B) 5 \\u092e\\u093f\\u0928\\u091f C) 18 \\u092e\\u093f\\u0928\\u091f D) 20 \\u092e\\u093f\\u0928\\u091f ### MCQ ### \"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Output\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"A\",\n          \"C\",\n          \"B\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sub-Domain\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 57,\n        \"samples\": [\n          \"college_medicine\",\n          \"security_studies\",\n          \"high_school_microeconomics\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Dataset\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"MMLU\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"tok\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 164,\n        \"min\": 29,\n        \"max\": 1917,\n        \"num_unique_values\": 831,\n        \"samples\": [\n          251\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"A1\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.22160853381381335,\n        \"min\": 0.0030818823724985123,\n        \"max\": 0.9918692111968994,\n        \"num_unique_values\": 13978,\n        \"samples\": [\n          0.771519124507904\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"A2\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.087638937111357e-06,\n        \"min\": 8.247686561491108e-11,\n        \"max\": 8.265939686680213e-05,\n        \"num_unique_values\": 13950,\n        \"samples\": [\n          1.7540160115459003e-06\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"A3\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.4004740855577997e-09,\n        \"min\": 0.0,\n        \"max\": 1.9559506370114832e-07,\n        \"num_unique_values\": 15,\n        \"samples\": [\n          2.3831270290486373e-09\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"B1\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.2339628634975501,\n        \"min\": 0.0009032916277647018,\n        \"max\": 0.9854469299316406,\n        \"num_unique_values\": 13978,\n        \"samples\": [\n          0.10441376268863678\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"B2\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 8.363127910536849e-07,\n        \"min\": 9.141065508699864e-12,\n        \"max\": 3.5694938560482115e-05,\n        \"num_unique_values\": 13967,\n        \"samples\": [\n          6.030485337760183e-07\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"B3\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.885658273906601e-09,\n        \"min\": 0.0,\n        \"max\": 1.421020670022699e-07,\n        \"num_unique_values\": 15,\n        \"samples\": [\n          1.4454397678775877e-09\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"C1\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.23410864197271353,\n        \"min\": 0.0004266847390681505,\n        \"max\": 0.9852486252784729,\n        \"num_unique_values\": 13977,\n        \"samples\": [\n          0.02871343493461609\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"C2\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 5.467039964131735e-07,\n        \"min\": 5.373755260218438e-12,\n        \"max\": 2.0974444851162843e-05,\n        \"num_unique_values\": 13960,\n        \"samples\": [\n          6.385050710377982e-08\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"C3\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.7235856749677566e-10,\n        \"min\": 0.0,\n        \"max\": 1.7090906467842615e-08,\n        \"num_unique_values\": 15,\n        \"samples\": [\n          7.268127211190745e-10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"D1\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.25372532892436744,\n        \"min\": 9.415777458343655e-05,\n        \"max\": 0.9850152730941772,\n        \"num_unique_values\": 13979,\n        \"samples\": [\n          0.016012368723750114\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"D2\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.2580792115870143e-07,\n        \"min\": 2.0280341642142652e-11,\n        \"max\": 2.1851135443284875e-06,\n        \"num_unique_values\": 13956,\n        \"samples\": [\n          3.4553593764030666e-07\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"D3\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.2897954282110254e-09,\n        \"min\": 0.0,\n        \"max\": 1.1066919824997967e-07,\n        \"num_unique_values\": 15,\n        \"samples\": [\n          4.995305835642228e-10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 73
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df['A'] = df['A1'] + df['A2'] + df['A3']\n",
+        "df['B'] = df['B1'] + df['B2'] + df['B3']\n",
+        "df['C'] = df['C1'] + df['C2'] + df['C3']\n",
+        "df['D'] = df['D1'] + df['D2'] + df['D3']"
+      ],
+      "metadata": {
+        "id": "z1sa1MNJ2Fo8"
+      },
+      "id": "z1sa1MNJ2Fo8",
+      "execution_count": 74,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df['ANS'] = df[['A', 'B', 'C', 'D']].idxmax(axis=1)"
+      ],
+      "metadata": {
+        "id": "c1bm0UDqohyP"
+      },
+      "id": "c1bm0UDqohyP",
+      "execution_count": 75,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df.head(10)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 565
+        },
+        "id": "jHJ5DCl4JwXl",
+        "outputId": "8ad9e506-3302-4c30-89df-b83f74cc1954"
+      },
+      "id": "jHJ5DCl4JwXl",
+      "execution_count": 76,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                                                   Input Output  \\\n",
+              "1262   सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...      B   \n",
+              "1202   सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...      A   \n",
+              "1289   सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...      A   \n",
+              "1246   सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...      D   \n",
+              "1358   सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...      D   \n",
+              "5938   यह प्रश्न निम्नलिखित जानकारी से संबंधित है।\\nस...      A   \n",
+              "5874   यह प्रश्न निम्नलिखित जानकारी से संबंधित है।\\nस...      B   \n",
+              "12115  साल 1993 में, एक पशुपालक किसान को 20 एकड़ के स...      A   \n",
+              "10876  एक भूमि-विकास कंपनी के पास दक्षिणपश्चिम में 40...      C   \n",
+              "11923  साल 1993 में, एक ज़मींदार के पास एक अंगूर के ब...      C   \n",
+              "\n",
+              "                      Sub-Domain Dataset   tok        A1            A2   A3  \\\n",
+              "1262            college_medicine    MMLU  1917  0.516257  3.852689e-07  0.0   \n",
+              "1202            college_medicine    MMLU  1894  0.954477  2.689888e-07  0.0   \n",
+              "1289            college_medicine    MMLU  1892  0.424950  2.352290e-07  0.0   \n",
+              "1246            college_medicine    MMLU  1831  0.225298  1.737284e-07  0.0   \n",
+              "1358            college_medicine    MMLU  1830  0.021581  6.391137e-08  0.0   \n",
+              "5938   high_school_world_history    MMLU  1313  0.831706  1.644773e-06  0.0   \n",
+              "5874   high_school_world_history    MMLU  1292  0.036370  8.827655e-07  0.0   \n",
+              "12115           professional_law    MMLU  1279  0.387942  3.234532e-05  0.0   \n",
+              "10876           professional_law    MMLU  1277  0.349803  1.543218e-05  0.0   \n",
+              "11923           professional_law    MMLU  1266  0.189858  6.847983e-06  0.0   \n",
+              "\n",
+              "             B1            B2  ...            C2   C3        D1            D2  \\\n",
+              "1262   0.354818  3.030374e-06  ...  2.790878e-08  0.0  0.069868  2.621788e-08   \n",
+              "1202   0.025436  2.689888e-07  ...  2.835121e-08  0.0  0.003442  2.053755e-09   \n",
+              "1289   0.121750  1.271636e-06  ...  5.947521e-08  0.0  0.424950  2.639196e-08   \n",
+              "1246   0.693966  3.455002e-07  ...  1.737284e-07  0.0  0.039151  1.339650e-08   \n",
+              "1358   0.917626  2.836049e-08  ...  1.831091e-08  0.0  0.031399  2.054427e-09   \n",
+              "5938   0.041408  1.203342e-06  ...  5.287115e-08  0.0  0.009239  1.514784e-08   \n",
+              "5874   0.937991  5.699563e-07  ...  1.534017e-07  0.0  0.003383  1.340409e-08   \n",
+              "12115  0.266629  6.369172e-06  ...  2.655066e-06  0.0  0.067414  1.824798e-06   \n",
+              "10876  0.349803  3.234760e-06  ...  6.369620e-07  0.0  0.100220  1.039812e-07   \n",
+              "11923  0.354702  1.626539e-06  ...  2.854664e-06  0.0  0.167549  5.621167e-07   \n",
+              "\n",
+              "        D3         A         B         C         D  ANS  \n",
+              "1262   0.0  0.516257  0.354821  0.048019  0.069868    A  \n",
+              "1202   0.0  0.954478  0.025436  0.012015  0.003442    A  \n",
+              "1289   0.0  0.424950  0.121751  0.021157  0.424950    A  \n",
+              "1246   0.0  0.225298  0.693966  0.030491  0.039151    B  \n",
+              "1358   0.0  0.021581  0.917626  0.021581  0.031399    B  \n",
+              "5938   0.0  0.831707  0.041409  0.112559  0.009239    A  \n",
+              "5874   0.0  0.036371  0.937992  0.017180  0.003383    B  \n",
+              "12115  0.0  0.387975  0.266635  0.266631  0.067416    A  \n",
+              "10876  0.0  0.349819  0.349806  0.187237  0.100220    A  \n",
+              "11923  0.0  0.189865  0.354704  0.276245  0.167550    B  \n",
+              "\n",
+              "[10 rows x 22 columns]"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-aea84745-cad7-4e10-9587-e7ab07fa148a\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Input</th>\n",
+              "      <th>Output</th>\n",
+              "      <th>Sub-Domain</th>\n",
+              "      <th>Dataset</th>\n",
+              "      <th>tok</th>\n",
+              "      <th>A1</th>\n",
+              "      <th>A2</th>\n",
+              "      <th>A3</th>\n",
+              "      <th>B1</th>\n",
+              "      <th>B2</th>\n",
+              "      <th>...</th>\n",
+              "      <th>C2</th>\n",
+              "      <th>C3</th>\n",
+              "      <th>D1</th>\n",
+              "      <th>D2</th>\n",
+              "      <th>D3</th>\n",
+              "      <th>A</th>\n",
+              "      <th>B</th>\n",
+              "      <th>C</th>\n",
+              "      <th>D</th>\n",
+              "      <th>ANS</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>1262</th>\n",
+              "      <td>सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>college_medicine</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1917</td>\n",
+              "      <td>0.516257</td>\n",
+              "      <td>3.852689e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.354818</td>\n",
+              "      <td>3.030374e-06</td>\n",
+              "      <td>...</td>\n",
+              "      <td>2.790878e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.069868</td>\n",
+              "      <td>2.621788e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.516257</td>\n",
+              "      <td>0.354821</td>\n",
+              "      <td>0.048019</td>\n",
+              "      <td>0.069868</td>\n",
+              "      <td>A</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1202</th>\n",
+              "      <td>सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>college_medicine</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1894</td>\n",
+              "      <td>0.954477</td>\n",
+              "      <td>2.689888e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.025436</td>\n",
+              "      <td>2.689888e-07</td>\n",
+              "      <td>...</td>\n",
+              "      <td>2.835121e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.003442</td>\n",
+              "      <td>2.053755e-09</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.954478</td>\n",
+              "      <td>0.025436</td>\n",
+              "      <td>0.012015</td>\n",
+              "      <td>0.003442</td>\n",
+              "      <td>A</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1289</th>\n",
+              "      <td>सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>college_medicine</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1892</td>\n",
+              "      <td>0.424950</td>\n",
+              "      <td>2.352290e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.121750</td>\n",
+              "      <td>1.271636e-06</td>\n",
+              "      <td>...</td>\n",
+              "      <td>5.947521e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.424950</td>\n",
+              "      <td>2.639196e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.424950</td>\n",
+              "      <td>0.121751</td>\n",
+              "      <td>0.021157</td>\n",
+              "      <td>0.424950</td>\n",
+              "      <td>A</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1246</th>\n",
+              "      <td>सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...</td>\n",
+              "      <td>D</td>\n",
+              "      <td>college_medicine</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1831</td>\n",
+              "      <td>0.225298</td>\n",
+              "      <td>1.737284e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.693966</td>\n",
+              "      <td>3.455002e-07</td>\n",
+              "      <td>...</td>\n",
+              "      <td>1.737284e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.039151</td>\n",
+              "      <td>1.339650e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.225298</td>\n",
+              "      <td>0.693966</td>\n",
+              "      <td>0.030491</td>\n",
+              "      <td>0.039151</td>\n",
+              "      <td>B</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1358</th>\n",
+              "      <td>सौना का उपयोग करना जिसे \"सौना स्नान\" या सौना ब...</td>\n",
+              "      <td>D</td>\n",
+              "      <td>college_medicine</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1830</td>\n",
+              "      <td>0.021581</td>\n",
+              "      <td>6.391137e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.917626</td>\n",
+              "      <td>2.836049e-08</td>\n",
+              "      <td>...</td>\n",
+              "      <td>1.831091e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.031399</td>\n",
+              "      <td>2.054427e-09</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.021581</td>\n",
+              "      <td>0.917626</td>\n",
+              "      <td>0.021581</td>\n",
+              "      <td>0.031399</td>\n",
+              "      <td>B</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5938</th>\n",
+              "      <td>यह प्रश्न निम्नलिखित जानकारी से संबंधित है।\\nस...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>high_school_world_history</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1313</td>\n",
+              "      <td>0.831706</td>\n",
+              "      <td>1.644773e-06</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.041408</td>\n",
+              "      <td>1.203342e-06</td>\n",
+              "      <td>...</td>\n",
+              "      <td>5.287115e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.009239</td>\n",
+              "      <td>1.514784e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.831707</td>\n",
+              "      <td>0.041409</td>\n",
+              "      <td>0.112559</td>\n",
+              "      <td>0.009239</td>\n",
+              "      <td>A</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5874</th>\n",
+              "      <td>यह प्रश्न निम्नलिखित जानकारी से संबंधित है।\\nस...</td>\n",
+              "      <td>B</td>\n",
+              "      <td>high_school_world_history</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1292</td>\n",
+              "      <td>0.036370</td>\n",
+              "      <td>8.827655e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.937991</td>\n",
+              "      <td>5.699563e-07</td>\n",
+              "      <td>...</td>\n",
+              "      <td>1.534017e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.003383</td>\n",
+              "      <td>1.340409e-08</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.036371</td>\n",
+              "      <td>0.937992</td>\n",
+              "      <td>0.017180</td>\n",
+              "      <td>0.003383</td>\n",
+              "      <td>B</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>12115</th>\n",
+              "      <td>साल 1993 में, एक पशुपालक किसान को 20 एकड़ के स...</td>\n",
+              "      <td>A</td>\n",
+              "      <td>professional_law</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1279</td>\n",
+              "      <td>0.387942</td>\n",
+              "      <td>3.234532e-05</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.266629</td>\n",
+              "      <td>6.369172e-06</td>\n",
+              "      <td>...</td>\n",
+              "      <td>2.655066e-06</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.067414</td>\n",
+              "      <td>1.824798e-06</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.387975</td>\n",
+              "      <td>0.266635</td>\n",
+              "      <td>0.266631</td>\n",
+              "      <td>0.067416</td>\n",
+              "      <td>A</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>10876</th>\n",
+              "      <td>एक भूमि-विकास कंपनी के पास दक्षिणपश्चिम में 40...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>professional_law</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1277</td>\n",
+              "      <td>0.349803</td>\n",
+              "      <td>1.543218e-05</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.349803</td>\n",
+              "      <td>3.234760e-06</td>\n",
+              "      <td>...</td>\n",
+              "      <td>6.369620e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.100220</td>\n",
+              "      <td>1.039812e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.349819</td>\n",
+              "      <td>0.349806</td>\n",
+              "      <td>0.187237</td>\n",
+              "      <td>0.100220</td>\n",
+              "      <td>A</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>11923</th>\n",
+              "      <td>साल 1993 में, एक ज़मींदार के पास एक अंगूर के ब...</td>\n",
+              "      <td>C</td>\n",
+              "      <td>professional_law</td>\n",
+              "      <td>MMLU</td>\n",
+              "      <td>1266</td>\n",
+              "      <td>0.189858</td>\n",
+              "      <td>6.847983e-06</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.354702</td>\n",
+              "      <td>1.626539e-06</td>\n",
+              "      <td>...</td>\n",
+              "      <td>2.854664e-06</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.167549</td>\n",
+              "      <td>5.621167e-07</td>\n",
+              "      <td>0.0</td>\n",
+              "      <td>0.189865</td>\n",
+              "      <td>0.354704</td>\n",
+              "      <td>0.276245</td>\n",
+              "      <td>0.167550</td>\n",
+              "      <td>B</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>10 rows × 22 columns</p>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-aea84745-cad7-4e10-9587-e7ab07fa148a')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-aea84745-cad7-4e10-9587-e7ab07fa148a button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-aea84745-cad7-4e10-9587-e7ab07fa148a');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-d2b0698b-48c2-4f79-b365-5b0f2468847e\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-d2b0698b-48c2-4f79-b365-5b0f2468847e')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-d2b0698b-48c2-4f79-b365-5b0f2468847e button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "variable_name": "df"
+            }
+          },
+          "metadata": {},
+          "execution_count": 76
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "accuracy = (df['Output'] == df['ANS']).mean()\n",
+        "print(f\"Accuracy: {accuracy:.4f}\")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "7o2o5J9Kotv_",
+        "outputId": "03880633-be9d-4b60-ee54-71374dde9cb4"
+      },
+      "id": "7o2o5J9Kotv_",
+      "execution_count": 77,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Accuracy: 0.5410\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df['ANS'].value_counts()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 241
+        },
+        "id": "BycMopmbIwlE",
+        "outputId": "25c60806-4f54-491b-9fe7-329049f59d14"
+      },
+      "id": "BycMopmbIwlE",
+      "execution_count": 78,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "ANS\n",
+              "B    4555\n",
+              "A    3429\n",
+              "D    3033\n",
+              "C    3025\n",
+              "Name: count, dtype: int64"
+            ],
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>count</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>ANS</th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>B</th>\n",
+              "      <td>4555</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>A</th>\n",
+              "      <td>3429</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>D</th>\n",
+              "      <td>3033</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>C</th>\n",
+              "      <td>3025</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div><br><label><b>dtype:</b> int64</label>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 78
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "for sd, group in df.groupby('Sub-Domain'):\n",
+        "    accuracy = (group['Output'] == group['ANS']).mean()\n",
+        "    print(f\"Sub-domain: {sd}, Accuracy: {accuracy:.4f}\")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "29c_ZVaRo2O2",
+        "outputId": "f93c913e-e9b9-448a-eaf3-5cbc34863b14"
+      },
+      "id": "29c_ZVaRo2O2",
+      "execution_count": 79,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Sub-domain: abstract_algebra, Accuracy: 0.3900\n",
+            "Sub-domain: anatomy, Accuracy: 0.4963\n",
+            "Sub-domain: astronomy, Accuracy: 0.5658\n",
+            "Sub-domain: business_ethics, Accuracy: 0.5200\n",
+            "Sub-domain: clinical_knowledge, Accuracy: 0.5736\n",
+            "Sub-domain: college_biology, Accuracy: 0.6181\n",
+            "Sub-domain: college_chemistry, Accuracy: 0.4900\n",
+            "Sub-domain: college_computer_science, Accuracy: 0.4800\n",
+            "Sub-domain: college_mathematics, Accuracy: 0.3200\n",
+            "Sub-domain: college_medicine, Accuracy: 0.5838\n",
+            "Sub-domain: college_physics, Accuracy: 0.4314\n",
+            "Sub-domain: computer_security, Accuracy: 0.6300\n",
+            "Sub-domain: conceptual_physics, Accuracy: 0.6170\n",
+            "Sub-domain: econometrics, Accuracy: 0.4035\n",
+            "Sub-domain: electrical_engineering, Accuracy: 0.5793\n",
+            "Sub-domain: elementary_mathematics, Accuracy: 0.4947\n",
+            "Sub-domain: formal_logic, Accuracy: 0.4286\n",
+            "Sub-domain: global_facts, Accuracy: 0.4100\n",
+            "Sub-domain: high_school_biology, Accuracy: 0.7258\n",
+            "Sub-domain: high_school_chemistry, Accuracy: 0.5419\n",
+            "Sub-domain: high_school_computer_science, Accuracy: 0.7300\n",
+            "Sub-domain: high_school_european_history, Accuracy: 0.6909\n",
+            "Sub-domain: high_school_geography, Accuracy: 0.6515\n",
+            "Sub-domain: high_school_government_and_politics, Accuracy: 0.6321\n",
+            "Sub-domain: high_school_macroeconomics, Accuracy: 0.5487\n",
+            "Sub-domain: high_school_mathematics, Accuracy: 0.3519\n",
+            "Sub-domain: high_school_microeconomics, Accuracy: 0.5798\n",
+            "Sub-domain: high_school_physics, Accuracy: 0.4040\n",
+            "Sub-domain: high_school_psychology, Accuracy: 0.7064\n",
+            "Sub-domain: high_school_statistics, Accuracy: 0.5185\n",
+            "Sub-domain: high_school_us_history, Accuracy: 0.6569\n",
+            "Sub-domain: high_school_world_history, Accuracy: 0.7764\n",
+            "Sub-domain: human_aging, Accuracy: 0.5561\n",
+            "Sub-domain: human_sexuality, Accuracy: 0.5725\n",
+            "Sub-domain: international_law, Accuracy: 0.6364\n",
+            "Sub-domain: jurisprudence, Accuracy: 0.6019\n",
+            "Sub-domain: logical_fallacies, Accuracy: 0.4294\n",
+            "Sub-domain: machine_learning, Accuracy: 0.3839\n",
+            "Sub-domain: management, Accuracy: 0.6117\n",
+            "Sub-domain: marketing, Accuracy: 0.8205\n",
+            "Sub-domain: medical_genetics, Accuracy: 0.5700\n",
+            "Sub-domain: miscellaneous, Accuracy: 0.6616\n",
+            "Sub-domain: moral_disputes, Accuracy: 0.5954\n",
+            "Sub-domain: moral_scenarios, Accuracy: 0.2547\n",
+            "Sub-domain: nutrition, Accuracy: 0.6275\n",
+            "Sub-domain: philosophy, Accuracy: 0.5627\n",
+            "Sub-domain: prehistory, Accuracy: 0.5679\n",
+            "Sub-domain: professional_accounting, Accuracy: 0.4610\n",
+            "Sub-domain: professional_law, Accuracy: 0.4192\n",
+            "Sub-domain: professional_medicine, Accuracy: 0.5184\n",
+            "Sub-domain: professional_psychology, Accuracy: 0.5327\n",
+            "Sub-domain: public_relations, Accuracy: 0.6636\n",
+            "Sub-domain: security_studies, Accuracy: 0.6490\n",
+            "Sub-domain: sociology, Accuracy: 0.6716\n",
+            "Sub-domain: us_foreign_policy, Accuracy: 0.5900\n",
+            "Sub-domain: virology, Accuracy: 0.4337\n",
+            "Sub-domain: world_religions, Accuracy: 0.6725\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "print(\"CLICK CTRl+S and wait for 2 sec\")\n",
+        "name = name.split('/')[-1]\n",
+        "name = name + \"-MMLU-H.ipynb\"\n",
+        "print(\"NOTEBOOK NAME SHOULD BE : \", name)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "m7vhP5Obk-sw",
+        "outputId": "8696f068-dba7-4b6f-c836-d2f7b49494ba"
+      },
+      "id": "m7vhP5Obk-sw",
+      "execution_count": 80,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "CLICK CTRl+S and wait for 2 sec\n",
+            "NOTEBOOK NAME SHOULD BE :  HINDI-GEMMA-9B-B10-MMLU-H.ipynb\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "c_5zVBU12crT"
+      },
+      "id": "c_5zVBU12crT",
+      "execution_count": 80,
+      "outputs": []
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.10.12"
+    },
+    "colab": {
+      "provenance": [],
+      "machine_shape": "hm",
+      "gpuType": "A100"
+    },
+    "accelerator": "GPU",
+    "widgets": {
+      "application/vnd.jupyter.widget-state+json": {
+        "e45f01941b984da59c8215e5d0fdbc33": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "VBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "VBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "VBoxView",
+            "box_style": "",
+            "children": [],
+            "layout": "IPY_MODEL_e8026b1bf4f948f7a67ab753bdc16565"
+          }
+        },
+        "c1af9f9962f14181b56af5c6340f41ad": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9a798dd18fca4140ae6d03085ae83629",
+            "placeholder": "​",
+            "style": "IPY_MODEL_5f2179c1a6314af88adca5856ed397f5",
+            "value": "<center> <img\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.svg\nalt='Hugging Face'> <br> Copy a token from <a\nhref=\"https://huggingface.co/settings/tokens\" target=\"_blank\">your Hugging Face\ntokens page</a> and paste it below. <br> Immediately click login after copying\nyour token or it might be stored in plain text in this notebook file. </center>"
+          }
+        },
+        "3381a25afa1a4ac4b65c531feb5f9407": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "PasswordModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "PasswordModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "PasswordView",
+            "continuous_update": true,
+            "description": "Token:",
+            "description_tooltip": null,
+            "disabled": false,
+            "layout": "IPY_MODEL_907d0f51a73748e9a7cda50e7bb58c35",
+            "placeholder": "​",
+            "style": "IPY_MODEL_78736d1cec3f4bcc9d2a59672ee4bb40",
+            "value": ""
+          }
+        },
+        "ade207c5bb44485dae09a5a3fc414bfb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "CheckboxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "CheckboxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "CheckboxView",
+            "description": "Add token as git credential?",
+            "description_tooltip": null,
+            "disabled": false,
+            "indent": true,
+            "layout": "IPY_MODEL_84e2f6d79bb04e388fd6053fc0207efd",
+            "style": "IPY_MODEL_7fa40ed7a38b4924902dfe6c1ff952f8",
+            "value": true
+          }
+        },
+        "96f8ae744112403aa1c2415772cf5faf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ButtonModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ButtonModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ButtonView",
+            "button_style": "",
+            "description": "Login",
+            "disabled": false,
+            "icon": "",
+            "layout": "IPY_MODEL_904403c8a1334588bee0c629a8518a5d",
+            "style": "IPY_MODEL_da9cc5f3770547759a5366c3410bf23b",
+            "tooltip": ""
+          }
+        },
+        "1f51d19ea1d84b0aa8d7635e873eb8fb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8bebf7a327364c05b04aae6d5def58ff",
+            "placeholder": "​",
+            "style": "IPY_MODEL_91105ed7122b4dfd9619f181ba8a838a",
+            "value": "\n<b>Pro Tip:</b> If you don't already have one, you can create a dedicated\n'notebooks' token with 'write' access, that you can then easily reuse for all\nnotebooks. </center>"
+          }
+        },
+        "e8026b1bf4f948f7a67ab753bdc16565": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": "center",
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "flex",
+            "flex": null,
+            "flex_flow": "column",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": "50%"
+          }
+        },
+        "9a798dd18fca4140ae6d03085ae83629": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5f2179c1a6314af88adca5856ed397f5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "907d0f51a73748e9a7cda50e7bb58c35": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "78736d1cec3f4bcc9d2a59672ee4bb40": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "84e2f6d79bb04e388fd6053fc0207efd": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7fa40ed7a38b4924902dfe6c1ff952f8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "904403c8a1334588bee0c629a8518a5d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "da9cc5f3770547759a5366c3410bf23b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ButtonStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ButtonStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "button_color": null,
+            "font_weight": ""
+          }
+        },
+        "8bebf7a327364c05b04aae6d5def58ff": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "91105ed7122b4dfd9619f181ba8a838a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "1511905fb6244d319a5d571c6f0d718d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "LabelModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "LabelModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "LabelView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a1d5b347418e473793ef7496bc9a6e21",
+            "placeholder": "​",
+            "style": "IPY_MODEL_45463d2f2148403c9ce4a8d743ba2925",
+            "value": "Connecting..."
+          }
+        },
+        "a1d5b347418e473793ef7496bc9a6e21": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "45463d2f2148403c9ce4a8d743ba2925": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "174f06d96a414316a2312c09f34f712e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_c08ac93850bb4e0da4e615d5a2c54ea0",
+              "IPY_MODEL_64bfcdc6238144659413b70f23ecd225",
+              "IPY_MODEL_450ee7e1025a4a72b6d0829c3a2b3f63"
+            ],
+            "layout": "IPY_MODEL_cc936c061dc24a378944f0789480f71e"
+          }
+        },
+        "c08ac93850bb4e0da4e615d5a2c54ea0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_af075b28873e440baeca0d3bd1326568",
+            "placeholder": "​",
+            "style": "IPY_MODEL_d7e0bbd0c277432d9f401168e157ad8d",
+            "value": "model.safetensors.index.json: 100%"
+          }
+        },
+        "64bfcdc6238144659413b70f23ecd225": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_20577fc6bce047979e0a00436ccbd4b5",
+            "max": 39072,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_0d1200471c634cb88c35131fb6bb8138",
+            "value": 39072
+          }
+        },
+        "450ee7e1025a4a72b6d0829c3a2b3f63": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f6710c96595c40d7868f341f2c12fc83",
+            "placeholder": "​",
+            "style": "IPY_MODEL_bd3c8bd7b391470e8a4f73f9ffa7b3a4",
+            "value": " 39.1k/39.1k [00:00&lt;00:00, 3.01MB/s]"
+          }
+        },
+        "cc936c061dc24a378944f0789480f71e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "af075b28873e440baeca0d3bd1326568": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d7e0bbd0c277432d9f401168e157ad8d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "20577fc6bce047979e0a00436ccbd4b5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0d1200471c634cb88c35131fb6bb8138": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "f6710c96595c40d7868f341f2c12fc83": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bd3c8bd7b391470e8a4f73f9ffa7b3a4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "524de86a695f480eb439a8fd86b21864": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_6b3f49b308184d2c8ebbf9e147412404",
+              "IPY_MODEL_53f83486f9d745b0a624b05d07ba3d8d",
+              "IPY_MODEL_7311811bb4bb46908a296fca1ede115b"
+            ],
+            "layout": "IPY_MODEL_204838c48ca7472e9ebf7dbf33634eb0"
+          }
+        },
+        "6b3f49b308184d2c8ebbf9e147412404": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4325dadbd09b4dc29da3c0a85bc5fd7f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_05ca7a0b6350455d89a717ddc2e63a85",
+            "value": "Downloading shards: 100%"
+          }
+        },
+        "53f83486f9d745b0a624b05d07ba3d8d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c090b7a2afac4fcb984b01087222a3f9",
+            "max": 4,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_3833525d061a4a0e9a7a79611122efc0",
+            "value": 4
+          }
+        },
+        "7311811bb4bb46908a296fca1ede115b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_84c0a4007be04b61bafcef174ec69371",
+            "placeholder": "​",
+            "style": "IPY_MODEL_772ee62e61b74b2d9fcb61c7c2d286f7",
+            "value": " 4/4 [07:19&lt;00:00, 105.73s/it]"
+          }
+        },
+        "204838c48ca7472e9ebf7dbf33634eb0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4325dadbd09b4dc29da3c0a85bc5fd7f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "05ca7a0b6350455d89a717ddc2e63a85": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c090b7a2afac4fcb984b01087222a3f9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3833525d061a4a0e9a7a79611122efc0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "84c0a4007be04b61bafcef174ec69371": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "772ee62e61b74b2d9fcb61c7c2d286f7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "68c533ea901a4c28920b1112b93de258": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_c188d0af85324681b5064cdac2ba2f31",
+              "IPY_MODEL_b85ae7b8519640c0a7c9583ed2a8b23f",
+              "IPY_MODEL_df07a8783e864ffd8b772cff27fb5b28"
+            ],
+            "layout": "IPY_MODEL_79a1cb526f4f4a11a940d78b6f3097c4"
+          }
+        },
+        "c188d0af85324681b5064cdac2ba2f31": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a93a629d55334109adaf15782e9065cf",
+            "placeholder": "​",
+            "style": "IPY_MODEL_06b4cbd683da47c8a50afe0065a51151",
+            "value": "model-00001-of-00004.safetensors: 100%"
+          }
+        },
+        "b85ae7b8519640c0a7c9583ed2a8b23f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_472bd364bafb4867a8f9e9f899cbc25e",
+            "max": 4903351912,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_e887923a42a942beae899f70429fe491",
+            "value": 4903351912
+          }
+        },
+        "df07a8783e864ffd8b772cff27fb5b28": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3cc7b6773e0543bc836e4595d2ed7bfe",
+            "placeholder": "​",
+            "style": "IPY_MODEL_25be37999c2545ed8c96a2ce60742cee",
+            "value": " 4.90G/4.90G [01:56&lt;00:00, 41.9MB/s]"
+          }
+        },
+        "79a1cb526f4f4a11a940d78b6f3097c4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a93a629d55334109adaf15782e9065cf": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "06b4cbd683da47c8a50afe0065a51151": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "472bd364bafb4867a8f9e9f899cbc25e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e887923a42a942beae899f70429fe491": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "3cc7b6773e0543bc836e4595d2ed7bfe": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "25be37999c2545ed8c96a2ce60742cee": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "a372bd6011b84c45a97e148bdc9695fc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_7cc3464f772b4dacb91f8ce218d342c3",
+              "IPY_MODEL_52804bc114fe46a0b40d553d42a38244",
+              "IPY_MODEL_c76fa847be0746b4b4ee90ab451fc7f6"
+            ],
+            "layout": "IPY_MODEL_a20ccdaa397c4f348b96777cd7f11960"
+          }
+        },
+        "7cc3464f772b4dacb91f8ce218d342c3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2b3a85edad614340ba341d2c072d649a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_7f69070804d742cdaae1d2c66563e1ed",
+            "value": "model-00002-of-00004.safetensors: 100%"
+          }
+        },
+        "52804bc114fe46a0b40d553d42a38244": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8bf0d5ca3a2c40b6a6d78f419acf5e5a",
+            "max": 4947570872,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_4403117d959742f6ae9c6efe6f77ed4f",
+            "value": 4947570872
+          }
+        },
+        "c76fa847be0746b4b4ee90ab451fc7f6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6ebd10dc63c34f4ba578409f24149e94",
+            "placeholder": "​",
+            "style": "IPY_MODEL_6edb9d21018a492ba8fb3ea85372946f",
+            "value": " 4.95G/4.95G [01:57&lt;00:00, 42.6MB/s]"
+          }
+        },
+        "a20ccdaa397c4f348b96777cd7f11960": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2b3a85edad614340ba341d2c072d649a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7f69070804d742cdaae1d2c66563e1ed": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "8bf0d5ca3a2c40b6a6d78f419acf5e5a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4403117d959742f6ae9c6efe6f77ed4f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "6ebd10dc63c34f4ba578409f24149e94": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6edb9d21018a492ba8fb3ea85372946f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "bc89f3e60fa84bf691e9730faa488954": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_b4cb31a854374e32bf3f4341c5d3e284",
+              "IPY_MODEL_b247dbbce0654ae8a58aa392c239c39d",
+              "IPY_MODEL_9d6f6ae615aa4fa3a5aed82f7fe1cf8d"
+            ],
+            "layout": "IPY_MODEL_e029ea34ff034b32b76f0a844abb097e"
+          }
+        },
+        "b4cb31a854374e32bf3f4341c5d3e284": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e8f6511b33bc4013834552ec36806919",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ae11e1bb9b54410290b8274857a8348d",
+            "value": "model-00003-of-00004.safetensors: 100%"
+          }
+        },
+        "b247dbbce0654ae8a58aa392c239c39d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6ce22946f266497c8a7b96b877a6acfb",
+            "max": 4962221464,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_3719bb61e1a3492eb990401878947bac",
+            "value": 4962221464
+          }
+        },
+        "9d6f6ae615aa4fa3a5aed82f7fe1cf8d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c43c34123f644b4682a47526d11d88e2",
+            "placeholder": "​",
+            "style": "IPY_MODEL_68a99f03b6fc4b92971f82d03f7623f0",
+            "value": " 4.96G/4.96G [01:58&lt;00:00, 42.1MB/s]"
+          }
+        },
+        "e029ea34ff034b32b76f0a844abb097e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e8f6511b33bc4013834552ec36806919": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ae11e1bb9b54410290b8274857a8348d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "6ce22946f266497c8a7b96b877a6acfb": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3719bb61e1a3492eb990401878947bac": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "c43c34123f644b4682a47526d11d88e2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "68a99f03b6fc4b92971f82d03f7623f0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "77af006fd0f74080a44923315a08acb2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_d3607cb4d41345208edc57807b912e09",
+              "IPY_MODEL_b514a8e63d6d47da8ac3627decef89cc",
+              "IPY_MODEL_2223c3227ba74fc695a3d32f04b829ec"
+            ],
+            "layout": "IPY_MODEL_a849ad5387694694b20a2f703a86bf0d"
+          }
+        },
+        "d3607cb4d41345208edc57807b912e09": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f011cc7c7c37423b8e937c6de0481de6",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2ec8db6289e7471c8a71a0ff87b6f8a2",
+            "value": "model-00004-of-00004.safetensors: 100%"
+          }
+        },
+        "b514a8e63d6d47da8ac3627decef89cc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_88d34e1c0cb5447e983b11fb085eb97a",
+            "max": 3670322200,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_43c4b99c0d374f13b89e6eee5af8f482",
+            "value": 3670322200
+          }
+        },
+        "2223c3227ba74fc695a3d32f04b829ec": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_81f63c0ad2d64e1c86da9f4e763946dc",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9f69f8bea863455b997b0685c9028c3f",
+            "value": " 3.67G/3.67G [01:26&lt;00:00, 42.1MB/s]"
+          }
+        },
+        "a849ad5387694694b20a2f703a86bf0d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f011cc7c7c37423b8e937c6de0481de6": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2ec8db6289e7471c8a71a0ff87b6f8a2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "88d34e1c0cb5447e983b11fb085eb97a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "43c4b99c0d374f13b89e6eee5af8f482": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "81f63c0ad2d64e1c86da9f4e763946dc": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9f69f8bea863455b997b0685c9028c3f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "915431f1bd894b86a5a1dea133f7cb3b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_fe522ed5ca7c45a48e3e1c046db6bdba",
+              "IPY_MODEL_37702074c4254f6eb6dc9df61cbb858e",
+              "IPY_MODEL_8b16b87e7c6c4abd82257f56b8972eb3"
+            ],
+            "layout": "IPY_MODEL_6f819b18d65541cfab2be05a7eb8b274"
+          }
+        },
+        "fe522ed5ca7c45a48e3e1c046db6bdba": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_46ab79f0e8d4499792faa9876f9b3ff0",
+            "placeholder": "​",
+            "style": "IPY_MODEL_0c549289db31454f9671a835cc45f16e",
+            "value": "Loading checkpoint shards: 100%"
+          }
+        },
+        "37702074c4254f6eb6dc9df61cbb858e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_18ae43ac56a441b1a98f37569fd6d177",
+            "max": 4,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_97ec184119fd4af194f16b7a8ecfa053",
+            "value": 4
+          }
+        },
+        "8b16b87e7c6c4abd82257f56b8972eb3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_14a438bd0f324e4a91866162cc86c85c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_d01d21b04daa491eb39a81ee26a7fc33",
+            "value": " 4/4 [00:07&lt;00:00,  1.82s/it]"
+          }
+        },
+        "6f819b18d65541cfab2be05a7eb8b274": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "46ab79f0e8d4499792faa9876f9b3ff0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0c549289db31454f9671a835cc45f16e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "18ae43ac56a441b1a98f37569fd6d177": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "97ec184119fd4af194f16b7a8ecfa053": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "14a438bd0f324e4a91866162cc86c85c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d01d21b04daa491eb39a81ee26a7fc33": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c85e7e8de6864d7398797ac306cfef98": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_8aed7f470993413aae78afc0a74b058b",
+              "IPY_MODEL_b60257c0af80409ba7bc7c550e5caa80",
+              "IPY_MODEL_5a1cc2a794654af1bce950fcd542fd15"
+            ],
+            "layout": "IPY_MODEL_3fcf65bf29d1449d88cebbdafea206e9"
+          }
+        },
+        "8aed7f470993413aae78afc0a74b058b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7cc17c2030ec4f41ac9e965ff11b14dd",
+            "placeholder": "​",
+            "style": "IPY_MODEL_a2f2db68c9194afca304e70b557b0e8e",
+            "value": "generation_config.json: 100%"
+          }
+        },
+        "b60257c0af80409ba7bc7c550e5caa80": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9570c5fefa01420e9bcc38e7385c6649",
+            "max": 190,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_63ad5215157d4a8fb0ada9cb86c94f03",
+            "value": 190
+          }
+        },
+        "5a1cc2a794654af1bce950fcd542fd15": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2ce0411a86eb46ac974d0da2f7d0c474",
+            "placeholder": "​",
+            "style": "IPY_MODEL_35cd05d06f4a4bc59437d65b7877a241",
+            "value": " 190/190 [00:00&lt;00:00, 19.1kB/s]"
+          }
+        },
+        "3fcf65bf29d1449d88cebbdafea206e9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7cc17c2030ec4f41ac9e965ff11b14dd": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a2f2db68c9194afca304e70b557b0e8e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9570c5fefa01420e9bcc38e7385c6649": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "63ad5215157d4a8fb0ada9cb86c94f03": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "2ce0411a86eb46ac974d0da2f7d0c474": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "35cd05d06f4a4bc59437d65b7877a241": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "56026e46c26c44e5804e9ffdec4a9ccb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_25efb39f5ea142f084a8696b43fa16cd",
+              "IPY_MODEL_1f6b6f1528534b4e80e5f00ad0c5c0b7",
+              "IPY_MODEL_a7a08996e9c64811b96c5cba473a614b"
+            ],
+            "layout": "IPY_MODEL_a363103e45e94eb0bee2046720ba2130"
+          }
+        },
+        "25efb39f5ea142f084a8696b43fa16cd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2a72200c88c74eb7b1051e2b9e13824d",
+            "placeholder": "​",
+            "style": "IPY_MODEL_82023240560045c1bf1f7dbe870386cf",
+            "value": "tokenizer_config.json: 100%"
+          }
+        },
+        "1f6b6f1528534b4e80e5f00ad0c5c0b7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_aaab672ca574454f95d0efbed97074d2",
+            "max": 47025,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_6408fe4dd2f24a2ba155aa801ee4d9be",
+            "value": 47025
+          }
+        },
+        "a7a08996e9c64811b96c5cba473a614b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8019199ec0ce4d878dd6e577e79813dc",
+            "placeholder": "​",
+            "style": "IPY_MODEL_113dc77b9b7d459ea9d7541ec2af46fd",
+            "value": " 47.0k/47.0k [00:00&lt;00:00, 4.34MB/s]"
+          }
+        },
+        "a363103e45e94eb0bee2046720ba2130": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2a72200c88c74eb7b1051e2b9e13824d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "82023240560045c1bf1f7dbe870386cf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "aaab672ca574454f95d0efbed97074d2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6408fe4dd2f24a2ba155aa801ee4d9be": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "8019199ec0ce4d878dd6e577e79813dc": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "113dc77b9b7d459ea9d7541ec2af46fd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2c4d26f10efd426f8d023c0560a77841": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_bb85706ab5df455f8e73d5fe7c623ca3",
+              "IPY_MODEL_d9f5bc779bfd42dfa03c6a32031255c1",
+              "IPY_MODEL_609d90e62e6743e8b006a975d3383715"
+            ],
+            "layout": "IPY_MODEL_a598b48e927f464e969ad419e46ca555"
+          }
+        },
+        "bb85706ab5df455f8e73d5fe7c623ca3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_679eac02c4244ec7810603c70ddda5a4",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ce458d53331c4a93892cfc23e0fc115a",
+            "value": "tokenizer.model: 100%"
+          }
+        },
+        "d9f5bc779bfd42dfa03c6a32031255c1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_048dfd2a045c49439c79734ac42e298f",
+            "max": 4241003,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_d7425e149bbb409080cd7affb8f31652",
+            "value": 4241003
+          }
+        },
+        "609d90e62e6743e8b006a975d3383715": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ea175e791098454cab0206e0023d9138",
+            "placeholder": "​",
+            "style": "IPY_MODEL_0f7fbd8af9474cb6a00fee4c34d57f3e",
+            "value": " 4.24M/4.24M [00:00&lt;00:00, 37.8MB/s]"
+          }
+        },
+        "a598b48e927f464e969ad419e46ca555": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "679eac02c4244ec7810603c70ddda5a4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ce458d53331c4a93892cfc23e0fc115a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "048dfd2a045c49439c79734ac42e298f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d7425e149bbb409080cd7affb8f31652": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "ea175e791098454cab0206e0023d9138": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0f7fbd8af9474cb6a00fee4c34d57f3e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9b7e202889914708b64ca8fd7fb447a2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_0083586e15fa407d822d41a7c11458a4",
+              "IPY_MODEL_b0f38f8eef314a1ca445ca3615b3fe8b",
+              "IPY_MODEL_5955f0ecb8824d78ad43a10695be1cc5"
+            ],
+            "layout": "IPY_MODEL_825c28f81a0548d8a33015be789154bf"
+          }
+        },
+        "0083586e15fa407d822d41a7c11458a4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8659f490215949499279c79a88f2f5f6",
+            "placeholder": "​",
+            "style": "IPY_MODEL_443f138f57b7475e86abb0440c7641f1",
+            "value": "special_tokens_map.json: 100%"
+          }
+        },
+        "b0f38f8eef314a1ca445ca3615b3fe8b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_134d957583334445a3beed87ed4e73d0",
+            "max": 636,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_022c835c4fdd4e70b4b5744139a34efd",
+            "value": 636
+          }
+        },
+        "5955f0ecb8824d78ad43a10695be1cc5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_619cfc09f622408e9cca7a75ae6d6932",
+            "placeholder": "​",
+            "style": "IPY_MODEL_10a0663b7fa54385a28fe38ba2dee207",
+            "value": " 636/636 [00:00&lt;00:00, 51.5kB/s]"
+          }
+        },
+        "825c28f81a0548d8a33015be789154bf": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8659f490215949499279c79a88f2f5f6": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "443f138f57b7475e86abb0440c7641f1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "134d957583334445a3beed87ed4e73d0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "022c835c4fdd4e70b4b5744139a34efd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "619cfc09f622408e9cca7a75ae6d6932": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "10a0663b7fa54385a28fe38ba2dee207": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "5deb72b8d7ca4b3da2bb497ca5e96b31": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HBoxModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_af97bf4c98d64bea9b1a32bde7295221",
+              "IPY_MODEL_04dba582b14d493583388ac07befa60c",
+              "IPY_MODEL_a40ea53e44144e3cb470d49d81d15727"
+            ],
+            "layout": "IPY_MODEL_33436687b7794410aa29d75217e23dfe"
+          }
+        },
+        "af97bf4c98d64bea9b1a32bde7295221": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_fb4d7013c5a94b2ab7e277011529a0f2",
+            "placeholder": "​",
+            "style": "IPY_MODEL_4427e78be36242bb8dddd20bb7034922",
+            "value": "tokenizer.json: 100%"
+          }
+        },
+        "04dba582b14d493583388ac07befa60c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "FloatProgressModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_92d6ac7839ba423b8c8c8e320b746089",
+            "max": 34362873,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_54a1a6c0c9f04093bbc6119323d76055",
+            "value": 34362873
+          }
+        },
+        "a40ea53e44144e3cb470d49d81d15727": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "HTMLModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6bcc3429e224490693bf89550210ceb9",
+            "placeholder": "​",
+            "style": "IPY_MODEL_0cb45c3824864477ac81407f43abf97f",
+            "value": " 34.4M/34.4M [00:00&lt;00:00, 42.2MB/s]"
+          }
+        },
+        "33436687b7794410aa29d75217e23dfe": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "fb4d7013c5a94b2ab7e277011529a0f2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4427e78be36242bb8dddd20bb7034922": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "92d6ac7839ba423b8c8c8e320b746089": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "54a1a6c0c9f04093bbc6119323d76055": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "ProgressStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "6bcc3429e224490693bf89550210ceb9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_name": "LayoutModel",
+          "model_module_version": "1.2.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0cb45c3824864477ac81407f43abf97f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_name": "DescriptionStyleModel",
+          "model_module_version": "1.5.0",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        }
+      }
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 5
+}
\ No newline at end of file