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162 lines
7.4 KiB
Markdown
162 lines
7.4 KiB
Markdown
# Text generation web UI
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A gradio web UI for running large language models like gpt-j-6B, gpt-neo, opt, galactica, and pygmalion on your own computer.
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Its goal is to become the [AUTOMATIC1111/stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui) of text generation.
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## Features
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* Switch between different models using a dropdown menu.
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* Generate nice HTML output for GPT-4chan.
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* Generate Markdown output for [GALACTICA](https://github.com/paperswithcode/galai), including LaTeX support.
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* Notebook mode that resembles OpenAI's playground.
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* Chat mode for conversation and role playing, including support for custom characters in JSON format.
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* Text output is streamed in real time.
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* Load parameter presets from text files.
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* Load large models in 8-bit mode.
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* Split large models across your GPU(s) and CPU.
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* CPU mode.
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* Get responses via API.
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* Works on Google Colab ([guide](https://github.com/oobabooga/text-generation-webui/wiki/Running-on-Colab)).
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## Installation
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1. You need to have the conda environment manager installed on your system. If you don't have it already, [get miniconda here](https://docs.conda.io/en/latest/miniconda.html).
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2. Open a terminal window and create a conda environment:
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```
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conda create -n textgen
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conda activate textgen
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```
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3. Install the appropriate pytorch. For NVIDIA GPUs, this should work:
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```
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conda install pytorch torchvision torchaudio pytorch-cuda=11.7 -c pytorch -c nvidia
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```
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For AMD GPUs, you need the ROCm version of pytorch.
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If you don't have a GPU and want to run the web UI in CPU mode, you just need the standard pytorch and should use this command instead:
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```
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conda install pytorch torchvision torchaudio -c pytorch
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```
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4. Clone or download this repository, and then `cd` into its folder from your terminal window.
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5. Install the required Python libraries:
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```
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pip install -r requirements.txt
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```
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After these steps, you should be able to start the web UI, but first you need to download some model to load.
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## Downloading models
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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).
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#### Hugging Face
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[Hugging Face](https://huggingface.co/models?pipeline_tag=text-generation&sort=downloads) is the main place to download models. These are some noteworthy examples:
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* [GPT-J 6B](https://huggingface.co/EleutherAI/gpt-j-6B/tree/main)
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* [GPT-Neo](https://huggingface.co/models?pipeline_tag=text-generation&sort=downloads&search=eleutherai+%2F+gpt-neo)
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* [OPT](https://huggingface.co/models?search=facebook/opt)
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* [GALACTICA](https://huggingface.co/models?search=facebook/galactica)
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* [\*-Erebus](https://huggingface.co/models?search=erebus)
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* [Pygmalion](https://huggingface.co/models?search=pygmalion)
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The files that you need to download are the json, txt, and pytorch\*.bin files. The remaining files are not necessary.
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For your convenience, you can automatically download a model from HF using the script `download-model.py`. Its usage is very simple:
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python download-model.py organization/model
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For instance:
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python download-model.py facebook/opt-1.3b
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#### GPT-4chan
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[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:
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* Torrent: [16-bit](https://archive.org/details/gpt4chan_model_float16) / [32-bit](https://archive.org/details/gpt4chan_model)
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* Direct download: [16-bit](https://theswissbay.ch/pdf/_notpdf_/gpt4chan_model_float16/) / [32-bit](https://theswissbay.ch/pdf/_notpdf_/gpt4chan_model/)
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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.
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After downloading the model, follow these steps:
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1. Place the files under `models/gpt4chan_model_float16` or `models/gpt4chan_model`.
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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).
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3. Download GPT-J 6B under `models/gpt-j-6B`:
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```
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python download-model.py EleutherAI/gpt-j-6B
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```
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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.
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#### Converting to pytorch (optional)
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The script `convert-to-torch.py` allows you to convert models to .pt format, which is about 10x faster to load to the GPU:
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python convert-to-torch.py models/model-name
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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`.
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## Starting the web UI
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conda activate textgen
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python server.py
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Then browse to
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`http://localhost:7860/?__theme=dark`
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Optionally, you can use the following command-line flags:
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| Flag | Description |
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|-------------|-------------|
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| `-h`, `--help` | show this help message and exit |
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| `--model MODEL` | Name of the model to load by default. |
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| `--notebook` | Launch the web UI in notebook mode, where the output is written to the same text box as the input. |
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| `--chat` | Launch the web UI in chat mode.|
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| `--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. |
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| `--cpu` | Use the CPU to generate text.|
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| `--load-in-8bit` | Load the model with 8-bit precision.|
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| `--auto-devices` | Automatically split the model across the available GPU(s) and CPU.|
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| `--disk` | If the model is too large for your GPU(s) and CPU combined, send the remaining layers to the disk. |
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| `--max-gpu-memory MAX_GPU_MEMORY` | Maximum memory in GiB to allocate to the GPU when loading the model. This is useful if you get out of memory errors while trying to generate text. Must be an integer number. |
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| `--no-stream` | Don't stream the text output in real time. This slightly improves the text generation performance.|
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| `--settings SETTINGS_FILE` | Load the default interface settings from this json file. See `settings-template.json` for an example.|
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| `--no-listen` | Make the web UI unreachable from your local network.|
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| `--share` | Create a public URL. This is useful for running the web UI on Google Colab or similar. |
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Out of memory errors? [Check this guide](https://github.com/oobabooga/text-generation-webui/wiki/Low-VRAM-guide).
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## Presets
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Inference settings presets can be created under `presets/` as text files. These files are detected automatically at startup.
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## System requirements
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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.
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## Contributing
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Pull requests, suggestions, and issue reports are welcome.
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## Credits
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- NovelAI and KoboldAI presets: https://github.com/KoboldAI/KoboldAI-Client/wiki/Settings-Presets
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- Pygmalion preset: https://github.com/PygmalionAI/gradio-ui/blob/master/src/gradio_ui.py
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- Verbose preset: Anonymous 4chan user.
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