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gpt4-x-vicuna-13B-GPTQ

Text Generation
Transformers
Safetensors
llama
text-generation-inference
4-bit precision
gptq
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license: other
inference: false
TheBlokeAI

gpt4-x-vicuna-13B-GPTQ

This repo contains 4bit GPTQ format quantised models of NousResearch's gpt4-x-vicuna-13b.

It is the result of quantising to 4bit using GPTQ-for-LLaMa.

Repositories available

How to easily download and use this model in text-generation-webui

Open the text-generation-webui UI as normal.

  1. Click the Model tab.
  2. Under Download custom model or LoRA, enter TheBloke/gpt4-x-vicuna-13B-GPTQ.
  3. Click Download.
  4. Wait until it says it's finished downloading.
  5. Click the Refresh icon next to Model in the top left.
  6. In the Model drop-down: choose the model you just downloaded, gpt4-x-vicuna-13B-GPTQ.
  7. If you see an error in the bottom right, ignore it - it's temporary.
  8. Fill out the GPTQ parameters on the right: Bits = 4, Groupsize = 128, model_type = Llama
  9. Click Save settings for this model in the top right.
  10. Click Reload the Model in the top right.
  11. Once it says it's loaded, click the Text Generation tab and enter a prompt!

Provided files

Compatible file - GPT4-x-Vicuna-13B-GPTQ-4bit-128g.compat.act-order.safetensors

In the main branch - the default one - you will find GPT4-x-Vicuna-13B-GPTQ-4bit-128g.compat.act-order.safetensors

This will work with all versions of GPTQ-for-LLaMa. It has maximum compatibility

It was created without the --act-order parameter. It may have slightly lower inference quality compared to the other file, but is guaranteed to work on all versions of GPTQ-for-LLaMa and text-generation-webui.

  • GPT4-x-Vicuna-13B-GPTQ-4bit-128g.compat.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
    • Parameters: Groupsize = 128g. No act-order.
    • Command used to create the GPTQ:
      CUDA_VISIBLE_DEVICES=0 python3 llama.py GPT4All-13B-snoozy c4 --wbits 4 --true-sequential --groupsize 128 --save_safetensors GPT4-x-Vicuna-13B-GPTQ-4bit-128g.compat.act-order.safetensors

Discord

For further support, and discussions on these models and AI in general, join us at:

TheBloke AI's Discord server

Thanks, and how to contribute.

Thanks to the chirper.ai team!

I've had a lot of people ask if they can contribute. I enjoy providing models and helping people, and would love to be able to spend even more time doing it, as well as expanding into new projects like fine tuning/training.

If you're able and willing to contribute it will be most gratefully received and will help me to keep providing more models, and to start work on new AI projects.

Donaters will get priority support on any and all AI/LLM/model questions and requests, access to a private Discord room, plus other benefits.

Patreon special mentions: Aemon Algiz, Dmitriy Samsonov, Nathan LeClaire, Trenton Dambrowitz, Mano Prime, David Flickinger, vamX, Nikolai Manek, senxiiz, Khalefa Al-Ahmad, Illia Dulskyi, Jonathan Leane, Talal Aujan, V. Lukas, Joseph William Delisle, Pyrater, Oscar Rangel, Lone Striker, Luke Pendergrass, Eugene Pentland, Sebastain Graf, Johann-Peter Hartman.

Thank you to all my generous patrons and donaters!

Original model card

As a base model used https://huggingface.co/eachadea/vicuna-13b-1.1

Finetuned on Teknium's GPTeacher dataset, unreleased Roleplay v2 dataset, GPT-4-LLM dataset, and Nous Research Instruct Dataset

Approx 180k instructions, all from GPT-4, all cleaned of any OpenAI censorship/"As an AI Language Model" etc.

Base model still has OpenAI censorship. Soon, a new version will be released with cleaned vicuna from https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltere

Trained on 8 A100-80GB GPUs for 5 epochs following Alpaca deepspeed training code.

Nous Research Instruct Dataset will be released soon.

GPTeacher, Roleplay v2 by https://huggingface.co/teknium

Wizard LM by https://github.com/nlpxucan

Nous Research Instruct Dataset by https://huggingface.co/karan4d and https://huggingface.co/huemin

Compute provided by our project sponsor https://redmond.ai/