3.0 KiB
text-generation-webui
A gradio webui for running large language models locally. Supports gpt-j-6B, gpt-neox-20b, opt, galactica, and many others.
Its goal is to become the AUTOMATIC1111/stable-diffusion-webui of text generation.
Installation
Create a conda environment:
conda create -n textgen
conda activate textgen
Install the appropriate pytorch for your GPU. For NVIDIA GPUs, this should work:
conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia
Install the requirements:
pip install -r requirements.txt
Downloading models
Models should be placed under models/model-name. For instance, models/gpt-j-6B for gpt-j-6B.
Hugging Face
Hugging Face is the main place to download models. These are some of my favorite:
The files that you need to download are the json, txt, and pytorch*.bin files. The remaining files are not necessary.
For your convenience, you can automatically download a model from HF using the script download-model.py. Its usage is very simple:
python download-model.py organization/model
For instance:
python download-model.py facebook/opt-1.3b
GPT-4chan
GPT-4chan has been shut down from Hugging Face, so you need to download it elsewhere. You have two options:
Converting to pytorch
The script convert-to-torch.py allows you to convert models to .pt format, which is about 10x faster to load:
python convert-to-torch.py models/model-name/
The output model will be saved to torch-dumps/model-name.pt. When you load a new model, the webui first looks for this .pt file; if it is not found, it loads the model as usual from models/model-name/.
Starting the webui
conda activate textgen
python server.py
Then browse to
http://localhost:7860/?__theme=dark
Optionally, you can use the following command-line flags:
--model model-name: Load this model by default.
--notebook: Launch the webui in notebook mode, where the output is written to the same text box as the input.
Presets
Inference settings presets can be created under presets/ as text files. These files are detected automatically at startup.
Contributing
Pull requests are welcome.