--- language: - en license: cc-by-nc-4.0 base_model: NeverSleep/Llama-3-Lumimaid-70B-v0.1 tags: - not-for-all-audiences - nsfw - exl2 --- ## Lumimaid 0.1 - EXL2 2.5bpw
This is a 2.5bpw EXL2 quant of [NeverSleep/Llama-3-Lumimaid-70B-v0.1](https://huggingface.co./NeverSleep/Llama-3-Lumimaid-70B-v0.1) Details about the model can be found at the above model page. ## EXL2 Version These quants were made with exllamav2 version 0.0.18. Quants made on this version of EXL2 may not work on older versions of the exllamav2 library. If you have problems loading these models, please update Text Generation WebUI to the latest version. ## 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 # Set the model name and bit size MODEL_NAME="Llama-3-Lumimaid-70B-v0.1" # Define variables MODEL_DIR="models/$MODEL_NAME" OUTPUT_DIR="exl2_$MODEL_NAME" MEASUREMENT_FILE="measurements/$MODEL_NAME.json" # Create the measurement file if needed if [ ! -f "$MEASUREMENT_FILE" ]; then echo "Creating $MEASUREMENT_FILE" # Create directories if [ -d "$OUTPUT_DIR" ]; then rm -r "$OUTPUT_DIR" fi mkdir "$OUTPUT_DIR" python convert.py -i $MODEL_DIR -o $OUTPUT_DIR -nr -om $MEASUREMENT_FILE fi # Choose one of the below. Either create a single quant for testing or a batch of them. BIT_PRECISIONS=(8.0 7.0 6.0 5.5 5.0 4.5 4.0 3.5 3.25 3.0 2.75 2.5 2.25) for BIT_PRECISION in "${BIT_PRECISIONS[@]}" do CONVERTED_FOLDER="models/${MODEL_NAME}_exl2_${BIT_PRECISION}bpw" # If it doesn't already exist, make the quant if [ ! -d "$CONVERTED_FOLDER" ]; then echo "Creating $CONVERTED_FOLDER" # Create directories if [ -d "$OUTPUT_DIR" ]; then rm -r "$OUTPUT_DIR" fi mkdir "$OUTPUT_DIR" mkdir "$CONVERTED_FOLDER" # Run conversion commands python convert.py -i $MODEL_DIR -o $OUTPUT_DIR -nr -m $MEASUREMENT_FILE -b $BIT_PRECISION -cf $CONVERTED_FOLDER fi done ```