File size: 3,410 Bytes
c6e456a b926638 023a3de c6e456a 85afc56 ccf4998 85afc56 b926638 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 |
---
license: gpl
inference: false
---
# gpt4-x-vicuna-13B-GPTQ
This repo contains 4bit GPTQ format quantised models of [NousResearch's gpt4-x-vicuna-13b](https://huggingface.co/NousResearch/gpt4-x-vicuna-13b).
It is the result of quantising to 4bit using [GPTQ-for-LLaMa](https://github.com/qwopqwop200/GPTQ-for-LLaMa).
## Repositories available
* [4bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/gpt4-x-vicuna-13B-GPTQ).
* [4bit and 5bit GGML models for CPU inference](https://huggingface.co/TheBloke/gpt4-x-vicuna-13B-GGML).
* [float16 model in HF format for GPU inference](https://huggingface.co/TheBloke/gpt4-x-vicuna-13B-HF).
## 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
```
# 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/ |