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README.md

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+---
+base_model: []
+library_name: transformers
+tags:
+- mergekit
+- merge
+---
+
+<div style="width: auto; margin-left: auto; margin-right: auto">
+<img src="https://i.imgur.com/Tn9MBg6.png" alt="MidnightMiqu" style="width: 100%; min-width: 400px; display: block; margin: auto;">
+</div>
+
+# Midnight-Miqu-70B-v1.5 - EXL2 4.5bpw
+
+This is a 4.5bpw EXL2 quant of [sophosympatheia/Midnight-Miqu-70B-v1.5](https://huggingface.co/sophosympatheia/Midnight-Miqu-70B-v1.5)
+
+Details about the model and the merge info can be found at the above mode page.
+
+I have not extensively tested this quant/model other than ensuring I could load it and chat with it.
+
+## Quant Details
+
+This is the script used for quantization.
+
+```bash
+#!/bin/bash
+
+# Activate the conda environment
+source ~/miniconda3/etc/profile.d/conda.sh
+conda activate exllamav2
+
+# Define variables
+MODEL_DIR="models/Midnight-Miqu-70B-v1.5"
+OUTPUT_DIR="exl2_midnightv15-70b"
+MEASUREMENT_FILE="measurements/midnight70b-v15.json"
+
+BIT_PRECISIONS=(6.0 5.0 4.5 4.0 3.5 3.0 2.65 2.4)
+
+for BIT_PRECISION in "${BIT_PRECISIONS[@]}"
+do
+    CONVERTED_FOLDER="models/Midnight-Miqu-70B-v1.5_exl2_${BIT_PRECISION}bpw"
+
+    if [ -d "$CONVERTED_FOLDER" ]; then
+        echo "Skipping $BIT_PRECISION as $CONVERTED_FOLDER already exists."
+        continue
+    fi
+
+    rm -r "$OUTPUT_DIR"
+    mkdir "$OUTPUT_DIR"
+    mkdir "$CONVERTED_FOLDER"
+    
+    python convert.py -i "$MODEL_DIR" -o "$OUTPUT_DIR" -nr -m "$MEASUREMENT_FILE" -b "$BIT_PRECISION" -cf "$CONVERTED_FOLDER"
+done
+```

config.json

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+{
+  "_name_or_path": "midnight-miqu-70b-v1.5",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 8192,
+  "initializer_range": 0.02,
+  "intermediate_size": 28672,
+  "max_position_embeddings": 32764,
+  "model_type": "llama",
+  "num_attention_heads": 64,
+  "num_hidden_layers": 80,
+  "num_key_value_heads": 8,
+  "pad_token_id": 0,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 1000000,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.36.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

mergekit_config.yml

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+merge_method: dare_linear
+base_model: /home/llm/mergequant/models/BASE/152334H_miqu-1-70b-sf # base model
+models:
+  - model: /home/llm/mergequant/models/midnight-miqu-70b-v1.0 # your merge goes here
+  - model: /home/llm/mergequant/models/BASE/Tess-70B-v1.6 # new "base model" goes here
+parameters:
+  weight: 1.0
+dtype: float16

model.safetensors.index.json

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