metadata

license: cc-by-nc-4.0
inference: false
pipeline_tag: text-generation
tags:
  - gguf
  - quantized
  - text-generation-inference

Credits:
Made with love by @Lewdiculous.
If this proves useful for you, feel free to credit and share the repository and authors.

Warning:
For Llama-3 models that don't follow the ChatML, Alpaca, Vicuna and other conventional formats, at the moment, you have to use gguf-imat-llama-3.py and replace the config files with the ones in the ChaoticNeutrals/Llama3-Corrections repository to properly quant and generate the imatrix data.

Pull Requests with your own features and improvements to this script are always welcome.

GGUF-IQ-Imatrix-Quantization-Script:

Simple python script (gguf-imat.py) to generate various GGUF-IQ-Imatrix quantizations from a Hugging Face author/model input, for Windows and NVIDIA hardware.

This is setup for a Windows machine with 8GB of VRAM, assuming use with an NVIDIA GPU. If you want to change the -ngl (number of GPU layers) amount, you can do so at line 124. This is only relevant during the --imatrix data generation. If you don't have enough VRAM you can decrease the -ngl amount or set it to 0 to only use your System RAM instead for all layers, this will make the imatrix data generation take longer, so it's a good idea to find the number that gives your own machine the best results.

Your imatrix.txt is expected to be located inside the imatrix folder. I have already included a file that is considered a good starting option, this discussion is where it came from. If you have suggestions or other imatrix data to recommend, please do so.

Adjust quantization_options in line 138.

Models downloaded to be used for quantization are cached at C:\Users\{{User}}\.cache\huggingface\hub. You can delete these files manually as needed after you're done with your quantizations, you can do it directly from your Terminal if you prefer with the rmdir "C:\Users\{{User}}\.cache\huggingface\hub" command. You can put it into another script or alias it to a convenient command if you prefer.

Hardware:

NVIDIA GPU with 8GB of VRAM.
32GB of system RAM.

Software Requirements:

Git
Python 3.11
- pip install huggingface_hub

Usage:

python .\gguf-imat.py

Quantizations will be output into the created models\{model-name}-GGUF folder.