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159 lines
8.0 KiB
Markdown
159 lines
8.0 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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**[Try it on Google Colab.](https://colab.research.google.com/github/oobabooga/AI-Notebooks/blob/main/Colab-TextGen-GPU.ipynb)**
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## Features
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* Switch between different models using a dropdown menu.
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* Notebook mode that resembles OpenAI's playground.
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* Chat mode for conversation and role playing.
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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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* Support for [Pygmalion](https://huggingface.co/models?search=pygmalionai/pygmalion) and custom characters in JSON format (just place the files under `characters/`).
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* Stream the text output 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), CPU, and disk.
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* CPU mode.
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* Get responses via API.
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* Works on Google Colab ([see the full guide](https://github.com/oobabooga/text-generation-webui/wiki/Running-on-Colab)).
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## Installation
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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):
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```
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conda create -n textgen
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conda activate textgen
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conda install pytorch torchvision torchaudio pytorch-cuda=11.7 git -c pytorch -c nvidia
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git clone https://github.com/oobabooga/text-generation-webui
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cd text-generation-webui
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pip install -r requirements.txt
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```
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The third line assumes that you have an NVIDIA GPU.
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* If you have an AMD GPU, you should install the ROCm version of pytorch instead.
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* If you are running in CPU mode, you just need the standard pytorch and should replace the third command with this one:
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```
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conda install pytorch torchvision torchaudio git -c pytorch
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```
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Once you have completed these steps, you should be able to start the web UI. However, you will first need to download a model.
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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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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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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.
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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 sometimes 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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| `--disk-cache-dir DISK_CACHE_DIR` | Directory to save the disk cache to. Defaults to `cache/`. |
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| `--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. |
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| `--cpu-memory CPU_MEMORY` | Maximum CPU memory in GiB to allocate for offloaded weights. Must be an integer number. Defaults to 99.|
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| `--no-stream` | Don't stream the text output in real time. This 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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| `--listen` | Make the web UI reachable 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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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.
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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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- Gradio dropdown menu refresh button: https://github.com/AUTOMATIC1111/stable-diffusion-webui
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