# 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](https://github.com/AUTOMATIC1111/stable-diffusion-webui) of text generation. ![webui screenshot](https://github.com/oobabooga/text-generation-webui/raw/main/webui.png) ## Features * Switch between different models using a dropdown menu. * Generate nice HTML output for GPT-4chan. * Generate Markdown output for [GALACTICA](https://github.com/paperswithcode/galai), including LaTeX support. * Notebook mode that resembles OpenAI's playground. * Chat mode for conversation and role playing. * Load 13b/20b models in 8-bit mode. * Load parameter presets from text files. * CPU mode. ## 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](https://huggingface.co/EleutherAI/gpt-j-6B/tree/main). #### Hugging Face Hugging Face is the main place to download models. These are some of my favorite: * [gpt-j-6B](https://huggingface.co/EleutherAI/gpt-j-6B/tree/main) * [gpt-neox-20b](https://huggingface.co/EleutherAI/gpt-neox-20b/tree/main) * [OPT](https://huggingface.co/models?search=facebook/opt) * [GALACTICA](https://huggingface.co/models?search=facebook/galactica) * [\*-Erebus](https://huggingface.co/models?search=erebus) 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](https://huggingface.co/ykilcher/gpt-4chan) has been shut down from Hugging Face, so you need to download it elsewhere. You have two options: * Torrent: [16-bit](https://archive.org/details/gpt4chan_model_float16) / [32-bit](https://archive.org/details/gpt4chan_model) * Direct download: [16-bit](https://theswissbay.ch/pdf/_notpdf_/gpt4chan_model_float16/) / [32-bit](https://theswissbay.ch/pdf/_notpdf_/gpt4chan_model/) You also need to put GPT-J-6B's config.json file in the same folder: [config.json](https://huggingface.co/EleutherAI/gpt-j-6B/raw/main/config.json) #### Converting to pytorch (optional) 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: -h, --help show this help message and exit --model MODEL Name of the model to load by default. --notebook Launch the webui in notebook mode, where the output is written to the same text box as the input. --chat Launch the webui in chat mode. --cpu Use the CPU to generate text. --listen Makes the webui reachable from your local network. ## Presets Inference settings presets can be created under `presets/` as text files. These files are detected automatically at startup. ## System requirements Check the [wiki](https://github.com/oobabooga/text-generation-webui/wiki/System-requirements) for some examples of VRAM and RAM usage in both GPU and CPU mode. ## Contributing Pull requests, suggestions and issue reports are welcome. ## Other projects Make sure to also check out the great work by [KoboldAI](https://github.com/KoboldAI/KoboldAI-Client). I have borrowed some of the presets listed on their [wiki](https://github.com/KoboldAI/KoboldAI-Client/wiki/Settings-Presets) after performing a k-means clustering analysis to select the most relevant subsample.