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README.md ADDED
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+ ---
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+ base_model: []
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+ library_name: transformers
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+ tags:
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+ - mergekit
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+ - merge
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+ ---
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+
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+ <div style="width: auto; margin-left: auto; margin-right: auto">
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+ <img src="https://i.imgur.com/Tn9MBg6.png" alt="MidnightMiqu" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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+ </div>
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+
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+ # Midnight-Miqu-70B-v1.5 - EXL2 2.5bpw
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+
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+ This is a 2.5bpw EXL2 quant of [sophosympatheia/Midnight-Miqu-70B-v1.5](https://huggingface.co/sophosympatheia/Midnight-Miqu-70B-v1.5)
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+
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+ Details about the model and the merge info can be found at the above mode page.
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+
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+ I have not extensively tested this quant/model other than ensuring I could load it and chat with it.
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+
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+ ## Quant Details
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+
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+ This is the script used for quantization.
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+
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+ ```bash
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+ #!/bin/bash
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+
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+ # Activate the conda environment
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+ source ~/miniconda3/etc/profile.d/conda.sh
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+ conda activate exllamav2
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+
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+ # Define variables
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+ MODEL_DIR="models/Midnight-Miqu-70B-v1.5"
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+ OUTPUT_DIR="exl2_midnightv15-70b"
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+ MEASUREMENT_FILE="measurements/midnight70b-v15.json"
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+
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+ BIT_PRECISIONS=(6.0 5.0 4.5 4.0 3.5 3.0 2.75 2.5 2.25)
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+
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+ for BIT_PRECISION in "${BIT_PRECISIONS[@]}"
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+ do
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+ CONVERTED_FOLDER="models/Midnight-Miqu-70B-v1.5_exl2_${BIT_PRECISION}bpw"
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+
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+ if [ -d "$CONVERTED_FOLDER" ]; then
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+ echo "Skipping $BIT_PRECISION as $CONVERTED_FOLDER already exists."
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+ continue
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+ fi
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+
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+ rm -r "$OUTPUT_DIR"
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+ mkdir "$OUTPUT_DIR"
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+ mkdir "$CONVERTED_FOLDER"
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+
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+ python convert.py -i "$MODEL_DIR" -o "$OUTPUT_DIR" -nr -m "$MEASUREMENT_FILE" -b "$BIT_PRECISION" -cf "$CONVERTED_FOLDER"
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+
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+ done```
config.json ADDED
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+ {
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+ "_name_or_path": "midnight-miqu-70b-v1.5",
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ ],
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+ "attention_bias": false,
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "hidden_act": "silu",
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+ "hidden_size": 8192,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 28672,
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+ "max_position_embeddings": 32764,
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+ "model_type": "llama",
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+ "num_attention_heads": 64,
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+ "num_hidden_layers": 80,
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+ "num_key_value_heads": 8,
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+ "pad_token_id": 0,
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+ "pretraining_tp": 1,
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+ "rms_norm_eps": 1e-05,
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+ "rope_scaling": null,
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+ "rope_theta": 1000000,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "float16",
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+ "transformers_version": "4.36.2",
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+ "use_cache": true,
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+ "vocab_size": 32000
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+ }
mergekit_config.yml ADDED
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+ merge_method: dare_linear
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+ base_model: /home/llm/mergequant/models/BASE/152334H_miqu-1-70b-sf # base model
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+ models:
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+ - model: /home/llm/mergequant/models/midnight-miqu-70b-v1.0 # your merge goes here
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+ - model: /home/llm/mergequant/models/BASE/Tess-70B-v1.6 # new "base model" goes here
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+ parameters:
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+ weight: 1.0
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+ dtype: float16
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