# 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](https://github.com/AUTOMATIC1111/stable-diffusion-webui) of text generation.

|![Image1](https://github.com/oobabooga/screenshots/raw/main/qa.png) | ![Image2](https://github.com/oobabooga/screenshots/raw/main/cai2.png) |
|:---:|:---:|
|![Image3](https://github.com/oobabooga/screenshots/raw/main/gpt4chan.png) | ![Image4](https://github.com/oobabooga/screenshots/raw/main/galactica.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, including support for custom characters in JSON format.
* Text output is streamed in real time.
* Load parameter presets from text files.
* Load large models in 8-bit mode.
* Split large models across your GPU(s) and CPU.
* CPU mode.
* Get responses via API.
* Works on Google Colab ([guide](https://github.com/oobabooga/text-generation-webui/wiki/Running-on-Colab)).

## Installation

Open a terminal and copy and paste these commands one at a time ([install conda](https://docs.conda.io/en/latest/miniconda.html) first if you don't have it already):

```
conda create -n textgen
conda activate textgen
conda install pytorch 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 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](https://huggingface.co/EleutherAI/gpt-j-6B/tree/main).

#### Hugging Face

[Hugging Face](https://huggingface.co/models?pipeline_tag=text-generation&sort=downloads) is the main place to download models. These are some noteworthy examples:

* [GPT-J 6B](https://huggingface.co/EleutherAI/gpt-j-6B/tree/main)
* [GPT-Neo](https://huggingface.co/models?pipeline_tag=text-generation&sort=downloads&search=eleutherai+%2F+gpt-neo)
* [OPT](https://huggingface.co/models?search=facebook/opt)
* [GALACTICA](https://huggingface.co/models?search=facebook/galactica)
* [\*-Erebus](https://huggingface.co/models?search=erebus)
* [Pygmalion](https://huggingface.co/models?search=pygmalion)

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/)

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](https://huggingface.co/EleutherAI/gpt-j-6B/raw/main/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 about 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 profile.png or profile.jpg exists in the same folder as server.py, this image will be used as the bot's 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 slightly improves the text generation performance.|
| `--settings SETTINGS_FILE` | Load the default interface settings from this json file. See `settings-template.json` for an example.|
| `--listen`   | Make the web UI reachable from your local network.|
| `--share`   | Create a public URL. This is useful for running the web UI on Google Colab or similar. |

Out of memory errors? [Check this guide](https://github.com/oobabooga/text-generation-webui/wiki/Low-VRAM-guide).

## 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.

## Credits

- NovelAI and KoboldAI presets: https://github.com/KoboldAI/KoboldAI-Client/wiki/Settings-Presets
- Pygmalion preset: https://github.com/PygmalionAI/gradio-ui/blob/master/src/gradio_ui.py
- Verbose preset: Anonymous 4chan user.
- Gradio dropdown menu refresh button: https://github.com/AUTOMATIC1111/stable-diffusion-webui