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license: other
inference: false

WizardLM: An Instruction-following LLM Using Evol-Instruct

These files are the result of merging the delta weights with the original Llama7B model.

The code for merging is provided in the WizardLM official Github repo.

WizardLM-7B 4bit GPTQ

This repo contains 4bit GPTQ models, quantised using GPTQ-for-LLaMa.

GIBBERISH OUTPUT IN text-generation-webui?

Please read the Provided Files section below. You should use wizardLM-7B-GPTQ-4bit-128g.no-act-order.safetensors unless you are able to use the latest GPTQ-for-LLaMa code.

If you're using a text-generation-webui one click installer, you MUST use wizardLM-7B-GPTQ-4bit-128g.no-act-order.safetensors.

Provided files

Two files are provided. The second file will not work unless you use a recent version of the Triton branch of GPTQ-for-LLaMa

Specifically, the second file uses --act-order for maximum quantisation quality and will not work with oobabooga's fork of GPTQ-for-LLaMa. Therefore at this time it will also not work with text-generation-webui one-click installers.

Unless you are able to use the latest Triton GPTQ-for-LLaMa code, please use medalpaca-13B-GPTQ-4bit-128g.no-act-order.safetensors

  • wizardLM-7B-GPTQ-4bit-128g.no-act-order.safetensors
    • Works with all versions of GPTQ-for-LLaMa code, both Triton and CUDA branches
    • Works with text-generation-webui one-click-installers
    • Works on Windows
    • Parameters: Groupsize = 128g. No act-order.
    • Command used to create the GPTQ:
      CUDA_VISIBLE_DEVICES=0 python3 llama.py wizardLM-7B-HF c4 --wbits 4 --true-sequential --groupsize 128 --save_safetensors wizardLM-7B-GPTQ-4bit-128g.no-act-order.safetensors
  • wizardLM-7B-GPTQ-4bit-128g.act-order.safetensors
    • Only works with recent GPTQ-for-LLaMa code
    • Does not work with text-generation-webui one-click-installers
    • Parameters: Groupsize = 128g. act-order.
    • Offers highest quality quantisation, but requires recent Triton GPTQ-for-LLaMa code and more VRAM
    • Command used to create the GPTQ:
      CUDA_VISIBLE_DEVICES=0 python3 llama.py wizardLM-7B-HF c4 --wbits 4 --true-sequential --act-order --groupsize 128 --save_safetensors wizardLM-7B-GPTQ-4bit-128g.act-order.safetensors

How to run in text-generation-webui

File wizardLM-7B-GPTQ-4bit-128g.no-act-order.safetensors can be loaded the same as any other GPTQ file, without requiring any updates to oobaboogas text-generation-webui.

Instructions on using GPTQ 4bit files in text-generation-webui are here.

The other two safetensors model files were created using --act-order to give the maximum possible quantisation quality, but this means it requires that the latest Triton GPTQ-for-LLaMa is used inside the UI.

If you want to use the act-order safetensors files and need to update the Triton branch of GPTQ-for-LLaMa, here are the commands I used to clone the Triton branch of GPTQ-for-LLaMa, clone text-generation-webui, and install GPTQ into the UI:

# Clone text-generation-webui, if you don't already have it
git clone https://github.com/oobabooga/text-generation-webui
# Make a repositories directory
mkdir text-generation-webui/repositories
cd text-generation-webui/repositories
# Clone the latest GPTQ-for-LLaMa code inside text-generation-webui
git clone https://github.com/qwopqwop200/GPTQ-for-LLaMa

Then install this model into text-generation-webui/models and launch the UI as follows:

cd text-generation-webui
python server.py --model medalpaca-13B-GPTQ-4bit --wbits 4 --groupsize 128 --model_type Llama # add any other command line args you want

The above commands assume you have installed all dependencies for GPTQ-for-LLaMa and text-generation-webui. Please see their respective repositories for further information.

If you can't update GPTQ-for-LLaMa or don't want to, you can use wizardLM-7B-GPTQ-4bit-128g.no-act-order.safetensors as mentioned above, which should work without any upgrades to text-generation-webui.

Original model info

Overview of Evol-Instruct Evol-Instruct is a novel method using LLMs instead of humans to automatically mass-produce open-domain instructions of various difficulty levels and skills range, to improve the performance of LLMs.

info