AI/text-generation-webui
1
0
Fork 0
mirror of https://github.com/oobabooga/text-generation-webui.git synced 2024-10-01 01:26:03 -04:00
Code Issues Packages Projects Releases Wiki Activity
90bb2caffd
text-generation-webui/README.md
oobabooga 90bb2caffd
Update README.md
2023-02-03 19:45:11 -03:00

8.9 KiB
Raw Blame History

Text generation web UI

A gradio web UI for running large language models like gpt-j-6B, gpt-neo, opt, galactica, and pygmalion on your own computer.

Its goal is to become the AUTOMATIC1111/stable-diffusion-webui of text generation.

[Try it on Google Colab] ---> Thanks to 81300, it now loads in 5 minutes instead of 12 <---

Image1 Image2
Image3 Image4

Features

  • Switch between different models using a dropdown menu.
  • Notebook mode that resembles OpenAI's playground.
  • Chat mode for conversation and role playing.
  • Generate nice HTML output for GPT-4chan.
  • Generate Markdown output for GALACTICA, including LaTeX support.
  • Support for Pygmalion and custom characters in JSON or TavernAI Character Card formats (FAQ).
  • Stream the text output in real time.
  • Load parameter presets from text files.
  • Load large models in 8-bit mode (see here if you are on Windows).
  • Split large models across your GPU(s), CPU, and disk.
  • CPU mode.
  • Get responses via API.
  • Support for extensions (guide).
  • Works on Google Colab (guide).

Installation

Open a terminal and copy and paste these commands one at a time (install conda first if you don't have it already):

conda create -n textgen
conda activate textgen
conda install torchvision torchaudio pytorch-cuda=11.7 git -c pytorch -c nvidia
git clone https://github.com/oobabooga/text-generation-webui
cd text-generation-webui
pip install -r requirements.txt

The third line assumes that you have an NVIDIA GPU.

  • If you have an AMD GPU, you should install the ROCm version of pytorch instead.
  • If you are running in CPU mode, you just need the standard pytorch and should replace the third command with this one:
conda install pytorch torchvision torchaudio git -c pytorch

Once you have completed these steps, you should be able to start the web UI. However, you will first need to download a model.

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 noteworthy examples:

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

If you want to download a model manually, note that all you need are the json, txt, and pytorch*.bin files. The remaining files are not necessary.

GPT-4chan

GPT-4chan has been shut down from Hugging Face, so you need to download it elsewhere. You have two options:

The 32-bit version is only relevant if you intend to run the model in CPU mode. Otherwise, you should use the 16-bit version.

After downloading the model, follow these steps:

  1. Place the files under models/gpt4chan_model_float16 or models/gpt4chan_model.
  2. Place GPT-J 6B's config.json file in that same folder: config.json.
  3. Download GPT-J 6B under models/gpt-j-6B:
python download-model.py EleutherAI/gpt-j-6B

You don't really need all of GPT-J 6B's files, just the tokenizer files, but you might as well download the whole thing. Those files will be automatically detected when you attempt to load GPT-4chan.

Converting to pytorch (optional)

The script convert-to-torch.py allows you to convert models to .pt format, which is sometimes 10x faster to load to the GPU:

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 web UI first looks for this .pt file; if it is not found, it loads the model as usual from models/model-name.

Starting the web UI

conda activate textgen
python server.py

Then browse to

http://localhost:7860/?__theme=dark

Optionally, you can use the following command-line flags:

Flag Description
-h, --help show this help message and exit
--model MODEL Name of the model to load by default.
--notebook Launch the web UI in notebook mode, where the output is written to the same text box as the input.
--chat Launch the web UI in chat mode.
--cai-chat Launch the web UI in chat mode with a style similar to Character.AI's. If the file img_bot.png or img_bot.jpg exists in the same folder as server.py, this image will be used as the bot's profile picture. Similarly, img_me.png or img_me.jpg will be used as your profile picture.
--cpu Use the CPU to generate text.
--load-in-8bit Load the model with 8-bit precision.
--auto-devices Automatically split the model across the available GPU(s) and CPU.
--disk If the model is too large for your GPU(s) and CPU combined, send the remaining layers to the disk.
--disk-cache-dir DISK_CACHE_DIR Directory to save the disk cache to. Defaults to cache/.
--gpu-memory GPU_MEMORY Maximum GPU memory in GiB to allocate. This is useful if you get out of memory errors while trying to generate text. Must be an integer number.
--cpu-memory CPU_MEMORY Maximum CPU memory in GiB to allocate for offloaded weights. Must be an integer number. Defaults to 99.
--no-stream Don't stream the text output in real time. This improves the text generation performance.
--settings SETTINGS_FILE Load the default interface settings from this json file. See settings-template.json for an example.
--extensions EXTENSIONS The list of extensions to load. If you want to load more than one extension, write the names separated by commas and between quotation marks, "like,this".
--listen Make the web UI reachable from your local network.
--listen-port LISTEN_PORT The listening port that the server will use.
--share Create a public URL. This is useful for running the web UI on Google Colab or similar.
--verbose Print the prompts to the terminal.

Out of memory errors? Check this guide.

Presets

Inference settings presets can be created under presets/ as text files. These files are detected automatically at startup.

By default, 10 presets by NovelAI and KoboldAI are included. These were selected out of a sample of 43 presets after applying a K-Means clustering algorithm and selecting the elements closest to the average of each cluster.

System requirements

Check the wiki for some examples of VRAM and RAM usage in both GPU and CPU mode.

Contributing

Pull requests, suggestions, and issue reports are welcome.

Before reporting a bug, make sure that you have created a conda environment and installed the dependencies exactly as in the Installation section above.

Credits