README.md

---
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 3.0bpw

This is a 3.0bpw 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 2.75 2.5 2.25)

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```