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new file mode 100644--- /dev/null
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+ "\u001b[?25hInstalling collected packages: pydub, xxhash, websockets, tomlkit, semantic-version, ruff, python-multipart, orjson, markupsafe, h11, ffmpy, dill, aiofiles, uvicorn, starlette, multiprocess, huggingface-hub, httpcore, httpx, fastapi, gradio-client, gradio, datasets\n",
+ " Attempting uninstall: markupsafe\n",
+ " Found existing installation: MarkupSafe 3.0.2\n",
+ " Uninstalling MarkupSafe-3.0.2:\n",
+ " Successfully uninstalled MarkupSafe-3.0.2\n",
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+ " Found existing installation: huggingface-hub 0.24.7\n",
+ " Uninstalling huggingface-hub-0.24.7:\n",
+ " Successfully uninstalled huggingface-hub-0.24.7\n",
+ "Successfully installed aiofiles-23.2.1 datasets-3.0.2 dill-0.3.8 fastapi-0.115.3 ffmpy-0.4.0 gradio-5.3.0 gradio-client-1.4.2 h11-0.14.0 httpcore-1.0.6 httpx-0.27.2 huggingface-hub-0.26.1 markupsafe-2.1.5 multiprocess-0.70.16 orjson-3.10.10 pydub-0.25.1 python-multipart-0.0.12 ruff-0.7.0 semantic-version-2.10.0 starlette-0.41.0 tomlkit-0.12.0 uvicorn-0.32.0 websockets-12.0 xxhash-3.5.0\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "!pip3 install torch==1.9.1+cu111 torchvision==0.10.1+cu111 torchaudio===0.9.1 -f https://download.pytorch.org/whl/torch_stable.html"
+ ],
+ "metadata": {
+ "id": "x5h0wugdaUEt",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "cba8efff-7126-41bc-b7db-50270fbea9a5",
+ "collapsed": true
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Looking in links: https://download.pytorch.org/whl/torch_stable.html\n",
+ "\u001b[31mERROR: Could not find a version that satisfies the requirement torch==1.9.1+cu111 (from versions: 1.11.0, 1.11.0+cpu, 1.11.0+cu102, 1.11.0+cu113, 1.11.0+cu115, 1.11.0+rocm4.3.1, 1.11.0+rocm4.5.2, 1.12.0, 1.12.0+cpu, 1.12.0+cu102, 1.12.0+cu113, 1.12.0+cu116, 1.12.0+rocm5.0, 1.12.0+rocm5.1.1, 1.12.1, 1.12.1+cpu, 1.12.1+cu102, 1.12.1+cu113, 1.12.1+cu116, 1.12.1+rocm5.0, 1.12.1+rocm5.1.1, 1.13.0, 1.13.0+cpu, 1.13.0+cu116, 1.13.0+cu117, 1.13.0+cu117.with.pypi.cudnn, 1.13.0+rocm5.1.1, 1.13.0+rocm5.2, 1.13.1, 1.13.1+cpu, 1.13.1+cu116, 1.13.1+cu117, 1.13.1+cu117.with.pypi.cudnn, 1.13.1+rocm5.1.1, 1.13.1+rocm5.2, 2.0.0, 2.0.0+cpu, 2.0.0+cpu.cxx11.abi, 2.0.0+cu117, 2.0.0+cu117.with.pypi.cudnn, 2.0.0+cu118, 2.0.0+rocm5.3, 2.0.0+rocm5.4.2, 2.0.1, 2.0.1+cpu, 2.0.1+cpu.cxx11.abi, 2.0.1+cu117, 2.0.1+cu117.with.pypi.cudnn, 2.0.1+cu118, 2.0.1+rocm5.3, 2.0.1+rocm5.4.2, 2.1.0, 2.1.0+cpu, 2.1.0+cpu.cxx11.abi, 2.1.0+cu118, 2.1.0+cu121, 2.1.0+cu121.with.pypi.cudnn, 2.1.0+rocm5.5, 2.1.0+rocm5.6, 2.1.1, 2.1.1+cpu, 2.1.1+cpu.cxx11.abi, 2.1.1+cu118, 2.1.1+cu121, 2.1.1+cu121.with.pypi.cudnn, 2.1.1+rocm5.5, 2.1.1+rocm5.6, 2.1.2, 2.1.2+cpu, 2.1.2+cpu.cxx11.abi, 2.1.2+cu118, 2.1.2+cu121, 2.1.2+cu121.with.pypi.cudnn, 2.1.2+rocm5.5, 2.1.2+rocm5.6, 2.2.0, 2.2.0+cpu, 2.2.0+cpu.cxx11.abi, 2.2.0+cu118, 2.2.0+cu121, 2.2.0+rocm5.6, 2.2.0+rocm5.7, 2.2.1, 2.2.1+cpu, 2.2.1+cpu.cxx11.abi, 2.2.1+cu118, 2.2.1+cu121, 2.2.1+rocm5.6, 2.2.1+rocm5.7, 2.2.2, 2.2.2+cpu, 2.2.2+cpu.cxx11.abi, 2.2.2+cu118, 2.2.2+cu121, 2.2.2+rocm5.6, 2.2.2+rocm5.7, 2.3.0, 2.3.0+cpu, 2.3.0+cpu.cxx11.abi, 2.3.0+cu118, 2.3.0+cu121, 2.3.0+rocm5.7, 2.3.0+rocm6.0, 2.3.1, 2.3.1+cpu, 2.3.1+cpu.cxx11.abi, 2.3.1+cu118, 2.3.1+cu121, 2.3.1+rocm5.7, 2.3.1+rocm6.0, 2.4.0, 2.4.1, 2.5.0)\u001b[0m\u001b[31m\n",
+ "\u001b[0m\u001b[31mERROR: No matching distribution found for torch==1.9.1+cu111\u001b[0m\u001b[31m\n",
+ "\u001b[0m"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "import torch\n",
+ "from transformers import AutoModelForSequenceClassification, AutoTokenizer, AutoConfig\n",
+ "import numpy as np\n",
+ "from scipy.special import softmax\n",
+ "import gradio as gr\n",
+ "torch.cuda.is_available()"
+ ],
+ "metadata": {
+ "id": "4D5DauxYbU98",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "7fff8e5e-528c-47a9-ec3a-1dfc7bac4fd3"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "False"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 4
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "model_path = \"cardiffnlp/twitter-roberta-base-sentiment-latest\"\n",
+ "\n",
+ "tokenizer = AutoTokenizer.from_pretrained(model_path)\n",
+ "config = AutoConfig.from_pretrained(model_path)\n",
+ "model = AutoModelForSequenceClassification.from_pretrained(model_path)\n"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 388,
+ "referenced_widgets": [
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+ },
+ "id": "-ZE1x72g3yv0",
+ "outputId": "3812b7a4-2743-46ef-c89c-c4e005551d92"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
+ "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
+ "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
+ "You will be able to reuse this secret in all of your notebooks.\n",
+ "Please note that authentication is recommended but still optional to access public models or datasets.\n",
+ " warnings.warn(\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "config.json: 0%| | 0.00/929 [00:00, ?B/s]"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "a14c64568ba049e6b28739c475adc716"
+ }
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "vocab.json: 0%| | 0.00/899k [00:00, ?B/s]"
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+ }
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "merges.txt: 0%| | 0.00/456k [00:00, ?B/s]"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "6cbfc431521e4c2ab72cd04fe39dfcff"
+ }
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "special_tokens_map.json: 0%| | 0.00/239 [00:00, ?B/s]"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "131b2531185f4f4ebdb2233ce364b96e"
+ }
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884\n",
+ " warnings.warn(\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "pytorch_model.bin: 0%| | 0.00/501M [00:00, ?B/s]"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "5ea9b4995ac2404bb2c99307f53d1d69"
+ }
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "Some weights of the model checkpoint at cardiffnlp/twitter-roberta-base-sentiment-latest were not used when initializing RobertaForSequenceClassification: ['roberta.pooler.dense.bias', 'roberta.pooler.dense.weight']\n",
+ "- This IS expected if you are initializing RobertaForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
+ "- This IS NOT expected if you are initializing RobertaForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "def sentiment_analysis(text):\n",
+ " encoded_input = tokenizer(text, return_tensors='pt')\n",
+ " output = model(**encoded_input)\n",
+ " scores_ = output[0][0].detach().numpy()\n",
+ " scores_ = softmax(scores_)\n",
+ " labels = ['Negative', 'Neutral', 'Positive']\n",
+ " scores = {l: float(s) for (l, s) in zip(labels, scores_)}\n",
+ " return scores\n"
+ ],
+ "metadata": {
+ "id": "OLwaFWJC4SmM"
+ },
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "demo = gr.Interface(\n",
+ " theme=gr.themes.Base(),\n",
+ " fn=sentiment_analysis,\n",
+ " inputs=gr.Textbox(placeholder=\"Write your text here...\"),\n",
+ " outputs=\"label\",\n",
+ " examples=[\n",
+ " [\"I'm thrilled about the job offer!\"],\n",
+ " [\"The weather today is absolutely beautiful.\"],\n",
+ " [\"I had a fantastic time at the concert last night.\"],\n",
+ " [\"I'm so frustrated with this software glitch.\"],\n",
+ " [\"The customer service was terrible at the store.\"],\n",
+ " [\"I'm really disappointed with the quality of this product.\"]\n",
+ " ],\n",
+ " title='Sentiment Analysis App',\n",
+ " description='This app classifies a positive, neutral, or negative sentiment.'\n",
+ ")\n"
+ ],
+ "metadata": {
+ "id": "u9rsf_mB4X3L"
+ },
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "demo.launch()\n"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 626
+ },
+ "id": "6mvik8xk4cPK",
+ "outputId": "a4fd1c34-2b0f-485b-9c8d-733893d23a19",
+ "collapsed": true
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Running Gradio in a Colab notebook requires sharing enabled. Automatically setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
+ "\n",
+ "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
+ "* Running on public URL: https://9604b3a1da7233cf45.gradio.live\n",
+ "\n",
+ "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ ""
+ ],
+ "text/html": [
+ ""
+ ]
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": []
+ },
+ "metadata": {},
+ "execution_count": 8
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "!ls\n",
+ "!git add app.py\n",
+ "!git commit -m \"app.py\"\n",
+ "#!git push\n",
+ "#!git push"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "oU0L06YkMquu",
+ "outputId": "39551554-72b7-49f6-c1dd-7db21c291b3f"
+ },
+ "execution_count": 10,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "sample_data Sentiment\n",
+ "fatal: not a git repository (or any of the parent directories): .git\n",
+ "fatal: not a git repository (or any of the parent directories): .git\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from transformers import AutoModelForSequenceClassification, AutoTokenizer\n",
+ "from huggingface_hub import notebook_login\n",
+ "\n",
+ "notebook_login()\n",
+ "\n",
+ "model.push_to_hub(\"Kiro0o/bert-sentiment-analysis\")\n",
+ "tokenizer.push_to_hub(\"Kiro0o/bert-sentiment-analysis\")\n"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 729,
+ "referenced_widgets": [
+ "062e07e9c999420eb7e6f353abc61279",
+ "e007d9d4dd8e428c900efe49f8bbb62c",
+ "0db7920e849d4e16b2d2a5f5afa7ef70",
+ "5611f16c6c784e64a00c60eb3b1b66bc",
+ "c4da6ebed3e64291a5f7fc12b9321914",
+ "4b1b4a677d68477d8605c0bb54a7c1bf",
+ "2250661a03064064b711e4a0035d3d08",
+ "73120158571e473d99fdd524ba882e98",
+ "e6925ba466a446fc941073f7b2304a69",
+ "98394977b70e40fbabb6aae1c5a90eb1",
+ "865fa016fa404ea989df576919c0e8cb",
+ "5f389c4848f044c6ba740c2302407e2f",
+ "84ff06aafc9f4e8ab45698e9bf05592d",
+ "b9c66bd1103c4fdaaec035b65cbad03a",
+ "aeff8c13fe0144afa122765e64ddb027",
+ "3ac16fc8511d4224a2b9360cc63379cb",
+ "187e28956eb542849218dc3feb9c6100"
+ ]
+ },
+ "id": "KASeNPFvcGs9",
+ "outputId": "bbd5ddc8-8437-4965-b588-b09aed42195c",
+ "collapsed": true
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "VBox(children=(HTML(value=' 406\u001b[0;31m \u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mraise_for_status\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 407\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mHTTPError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/requests/models.py\u001b[0m in \u001b[0;36mraise_for_status\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1023\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mhttp_error_msg\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1024\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mHTTPError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhttp_error_msg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1025\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mHTTPError\u001b[0m: 401 Client Error: Unauthorized for url: https://huggingface.co/api/repos/create",
+ "\nThe above exception was the direct cause of the following exception:\n",
+ "\u001b[0;31mHfHubHTTPError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mnotebook_login\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpush_to_hub\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Kiro0o/bert-sentiment-analysis\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 7\u001b[0m \u001b[0mtokenizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpush_to_hub\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Kiro0o/bert-sentiment-analysis\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py\u001b[0m in \u001b[0;36mpush_to_hub\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 2842\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mtags\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2843\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"tags\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtags\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2844\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpush_to_hub\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2845\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2846\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mget_memory_footprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreturn_buffers\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/transformers/utils/hub.py\u001b[0m in \u001b[0;36mpush_to_hub\u001b[0;34m(self, repo_id, use_temp_dir, commit_message, private, token, max_shard_size, create_pr, safe_serialization, revision, commit_description, tags, **deprecated_kwargs)\u001b[0m\n\u001b[1;32m 912\u001b[0m \u001b[0morganization\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdeprecated_kwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"organization\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 913\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 914\u001b[0;31m repo_id = self._create_repo(\n\u001b[0m\u001b[1;32m 915\u001b[0m \u001b[0mrepo_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprivate\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mprivate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtoken\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtoken\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrepo_url\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrepo_url\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morganization\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morganization\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 916\u001b[0m )\n",
+ "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/transformers/utils/hub.py\u001b[0m in \u001b[0;36m_create_repo\u001b[0;34m(self, repo_id, private, token, repo_url, organization)\u001b[0m\n\u001b[1;32m 728\u001b[0m \u001b[0mrepo_id\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34mf\"{organization}/{repo_id}\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 729\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 730\u001b[0;31m \u001b[0murl\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcreate_repo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrepo_id\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrepo_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtoken\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtoken\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprivate\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mprivate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexist_ok\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 731\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrepo_id\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 732\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_validators.py\u001b[0m in \u001b[0;36m_inner_fn\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 112\u001b[0m \u001b[0mkwargs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msmoothly_deprecate_use_auth_token\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn_name\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhas_token\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mhas_token\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 113\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 114\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 115\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 116\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0m_inner_fn\u001b[0m \u001b[0;31m# type: ignore\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/huggingface_hub/hf_api.py\u001b[0m in \u001b[0;36mcreate_repo\u001b[0;34m(self, repo_id, token, private, repo_type, exist_ok, resource_group_id, space_sdk, space_hardware, space_storage, space_sleep_time, space_secrets, space_variables)\u001b[0m\n\u001b[1;32m 3521\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3522\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3523\u001b[0;31m \u001b[0mhf_raise_for_status\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3524\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mHTTPError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3525\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mexist_ok\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstatus_code\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m409\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_http.py\u001b[0m in \u001b[0;36mhf_raise_for_status\u001b[0;34m(response, endpoint_name)\u001b[0m\n\u001b[1;32m 475\u001b[0m \u001b[0;31m# Convert `HTTPError` into a `HfHubHTTPError` to display request information\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 476\u001b[0m \u001b[0;31m# as well (request id and/or server error message)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 477\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0m_format\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mHfHubHTTPError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 478\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 479\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mHfHubHTTPError\u001b[0m: 401 Client Error: Unauthorized for url: https://huggingface.co/api/repos/create (Request ID: Root=1-6718bcf1-4e69449b3eaf5b654882be65;bdfa9c7d-94df-4e2f-b545-622461463289)\n\nInvalid username or password."
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "!git clone https://huggingface.co/spaces/Kiro0o/Sentiment"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "colUbn6_LI36",
+ "outputId": "8325afd4-3c60-452f-b8c8-443b012e3cd4"
+ },
+ "execution_count": 2,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Cloning into 'Sentiment'...\n",
+ "remote: Enumerating objects: 4, done.\u001b[K\n",
+ "remote: Total 4 (delta 0), reused 0 (delta 0), pack-reused 4 (from 1)\u001b[K\n",
+ "Unpacking objects: 100% (4/4), 1.29 KiB | 1.29 MiB/s, done.\n"
+ ]
+ }
+ ]
+ }
+ ]
+}
\ No newline at end of file
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