---
license: other
inference: false
---

# Alpaca LoRA GPTQ 4bit

This is a [GPTQ-for-LLaMa](https://github.com/qwopqwop200/GPTQ-for-LLaMa) [changsung's alpaca-lora-65B](https://huggingface.co/chansung/alpaca-lora-65b)

## These files need a lot of VRAM!

I believe they will work on 2 x 24GB cards, and I hope that at least the 1024g file will work on an A100 40GB.

I can't guarantee that the two 128g files will work in only 40GB of VRAM.

I haven't specifically tested VRAM requirements yet but will aim to do so at some point. If you have any experiences to share, please do so in the comments.

## GIBBERISH OUTPUT IN `text-generation-webui`?

Please read the Provided Files section below. You should use `alpaca-lora-65B-GPTQ-4bit-128g.no-act-order.safetensors` unless you are able to use the latest Triton branch of GPTQ-for-LLaMa.

## Provided files

Three files are provided. **The second and third files will not work unless you use a recent version of the Triton branch of GPTQ-for-LLaMa**

Specifically, the last two files use `--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 the CUDA branch of GPTQ-for-LLaMa, or `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`
 
* `alpaca-lora-65B-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
  * Will require ~40GB of VRAM, meaning you'll need an A100 or 2 x 24GB cards.
  * I haven't yet tested how much VRAM is required exactly so it's possible it won't run on an A100 
  * Parameters: Groupsize = 128g. No act-order.
  * Command used to create the GPTQ:
    ```
    CUDA_VISIBLE_DEVICES=0 python3 llama.py alpaca-lora-65B-HF c4 --wbits 4 --true-sequential --groupsize 128 --save_safetensors alpaca-lora-65B-GPTQ-4bit-128g.no-act-order.safetensors
    ```
* `alpaca-lora-65B-GPTQ-4bit-128g.safetensors`
  * Only works with the latest Triton branch of GPTQ-for-LLaMa
  * **Does not** work with text-generation-webui one-click-installers
  * **Does not** work on Windows
  * Will require 40+GB of VRAM, meaning you'll need an A100 or 2 x 24GB cards.
  * I haven't yet tested how much VRAM is required exactly so it's possible it won't run on an A100 40GB
  * 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 alpaca-lora-65B-HF c4 --wbits 4 --true-sequential --act-order --groupsize 128 --save_safetensors alpaca-lora-65B-GPTQ-4bit-128g.safetensors
    ```
* `alpaca-lora-65B-GPTQ-4bit-1024g.safetensors`
  * Only works with the latest Triton branch of GPTQ-for-LLaMa
  * **Does not** work with text-generation-webui one-click-installers
  * **Does not** work on Windows
  * Should require less VRAM than the 128g file, so hopefully will run in an A100 40GB
  * I haven't yet tested how much VRAM is required exactly
  * Parameters: Groupsize = 1024g. act-order.
  * Offers the benefits of act-order, but at a higher groupsize to reduce VRAM requirements
  * Command used to create the GPTQ:
    ```
    CUDA_VISIBLE_DEVICES=0 python3 llama.py alpaca-lora-65B-HF c4 --wbits 4 --true-sequential --act-order --groupsize 1024 --save_safetensors alpaca-lora-65B-GPTQ-4bit-1024g.safetensors
    ```

## How to run in `text-generation-webui`

File `alpaca-lora-65B-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](https://github.com/oobabooga/text-generation-webui).

[Instructions on using GPTQ 4bit files in text-generation-webui are here](https://github.com/oobabooga/text-generation-webui/wiki/GPTQ-models-\(4-bit-mode\)).

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 to the latest Triton branch, or don't want to, you can use `alpaca-lora-65B-GPTQ-4bit-128g.no-act-order.safetensors` as mentioned above, which should work without any upgrades to text-generation-webui.

# Original model card not provided

No model card was provided in [changsung's original repository](https://huggingface.co/chansung/alpaca-lora-65b).

Based on the name, I assume this is the result of fine tuning using the original GPT 3.5 Alpaca dataset. It is unknown as to whether the original Stanford data was used, or the [cleaned tloen/alpaca-lora variant](https://github.com/tloen/alpaca-lora).