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200 lines
12 KiB
Markdown
200 lines
12 KiB
Markdown
# Text generation web UI
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A gradio web UI for running Large Language Models like GPT-J 6B, OPT, GALACTICA, LLaMA, and Pygmalion.
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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 or TavernAI Character Card formats ([FAQ](https://github.com/oobabooga/text-generation-webui/wiki/Pygmalion-chat-model-FAQ)).
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* Advanced chat features (send images, get audio responses with TTS).
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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 (see [here](https://github.com/oobabooga/text-generation-webui/issues/147#issuecomment-1456040134), [here](https://github.com/oobabooga/text-generation-webui/issues/20#issuecomment-1411650652) and [here](https://www.reddit.com/r/PygmalionAI/comments/1115gom/running_pygmalion_6b_with_8gb_of_vram/) if you are on Windows).
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* Split large models across your GPU(s), CPU, and disk.
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* CPU mode.
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* [FlexGen offload](https://github.com/oobabooga/text-generation-webui/wiki/FlexGen).
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* [DeepSpeed ZeRO-3 offload](https://github.com/oobabooga/text-generation-webui/wiki/DeepSpeed).
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* Get responses via API, [with](https://github.com/oobabooga/text-generation-webui/blob/main/api-example-streaming.py) or [without](https://github.com/oobabooga/text-generation-webui/blob/main/api-example.py) streaming.
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* [Supports the LLaMA model, including 4-bit mode](https://github.com/oobabooga/text-generation-webui/wiki/LLaMA-model).
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* [Supports the RWKV model](https://github.com/oobabooga/text-generation-webui/wiki/RWKV-model).
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* Supports softprompts.
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* [Supports extensions](https://github.com/oobabooga/text-generation-webui/wiki/Extensions).
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* [Works on Google Colab](https://github.com/oobabooga/text-generation-webui/wiki/Running-on-Colab).
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## Installation option 1: conda
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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 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, replace the third command with this one:
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```
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pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/rocm5.2
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```
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* If you are running it in CPU mode, 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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> **Note**
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> 1. If you are on Windows, it may be easier to run the commands above in a WSL environment. The performance may also be better. A full guide can be found here: [Windows Subsystem for Linux (Ubuntu) Installation Guide
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](https://github.com/oobabooga/text-generation-webui/wiki/Windows-Subsystem-for-Linux-(Ubuntu)-Installation-Guide).
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> 2. For a more detailed, user-contributed guide, see: [Installation instructions for human beings](https://github.com/oobabooga/text-generation-webui/wiki/Installation-instructions-for-human-beings).
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## Installation option 2: one-click installers
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[oobabooga-windows.zip](https://github.com/oobabooga/one-click-installers/archive/refs/heads/oobabooga-windows.zip)
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[oobabooga-linux.zip](https://github.com/oobabooga/one-click-installers/archive/refs/heads/oobabooga-linux.zip)
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Just download the zip above, extract it, and double click on "install". The web UI and all its dependencies will be installed in the same folder.
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* To download a model, double click on "download-model"
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* To start the web UI, double click on "start-webui"
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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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* [Pythia](https://huggingface.co/models?search=eleutherai/pythia)
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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) (NSFW)
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* [Pygmalion](https://huggingface.co/models?search=pygmalion) (NSFW)
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You can automatically download a model from HF using the script `download-model.py`:
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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 (or model*.safetensors) 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's tokenizer files (they will be automatically detected when you attempt to load GPT-4chan):
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```
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python download-model.py EleutherAI/gpt-j-6B --text-only
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```
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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 `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. |
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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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| `--load-in-4bit` | DEPRECATED: use `--gptq-bits 4` instead. |
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| `--gptq-bits GPTQ_BITS` | Load a pre-quantized model with specified precision. 2, 3, 4 and 8 (bit) are supported. Currently only works with LLaMA and OPT. |
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| `--gptq-model-type MODEL_TYPE` | Model type of pre-quantized model. Currently only LLaMa and OPT are supported. |
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| `--bf16` | Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU. |
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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 [GPU_MEMORY ...]` | Maxmimum GPU memory in GiB to be allocated per GPU. Example: `--gpu-memory 10` for a single GPU, `--gpu-memory 10 5` for two GPUs. |
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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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| `--flexgen` | Enable the use of FlexGen offloading. |
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| `--percent PERCENT [PERCENT ...]` | FlexGen: allocation percentages. Must be 6 numbers separated by spaces (default: 0, 100, 100, 0, 100, 0). |
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| `--compress-weight` | FlexGen: Whether to compress weight (default: False).|
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| `--pin-weight [PIN_WEIGHT]` | FlexGen: whether to pin weights (setting this to False reduces CPU memory by 20%). |
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| `--deepspeed` | Enable the use of DeepSpeed ZeRO-3 for inference via the Transformers integration. |
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| `--nvme-offload-dir NVME_OFFLOAD_DIR` | DeepSpeed: Directory to use for ZeRO-3 NVME offloading. |
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| `--local_rank LOCAL_RANK` | DeepSpeed: Optional argument for distributed setups. |
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| `--rwkv-strategy RWKV_STRATEGY` | RWKV: The strategy to use while loading the model. Examples: "cpu fp32", "cuda fp16", "cuda fp16i8". |
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| `--rwkv-cuda-on` | RWKV: Compile the CUDA kernel for better performance. |
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| `--no-stream` | Don't stream the text output in real time. |
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| `--settings SETTINGS_FILE` | Load the default interface settings from this json file. See `settings-template.json` for an example. If you create a file called `settings.json`, this file will be loaded by default without the need to use the `--settings` flag.|
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| `--extensions EXTENSIONS [EXTENSIONS ...]` | The list of extensions to load. If you want to load more than one extension, write the names separated by spaces. |
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| `--listen` | Make the web UI reachable from your local network.|
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| `--listen-port LISTEN_PORT` | The listening port that the server will use. |
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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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| `--auto-launch` | Open the web UI in the default browser upon launch. |
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| `--verbose` | Print the prompts to the terminal. |
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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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Before reporting a bug, make sure that you have:
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1. Created a conda environment and installed the dependencies exactly as in the *Installation* section above.
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2. [Searched](https://github.com/oobabooga/text-generation-webui/issues) to see if an issue already exists for the issue you encountered.
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## Credits
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- Gradio dropdown menu refresh button: https://github.com/AUTOMATIC1111/stable-diffusion-webui
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- Verbose preset: Anonymous 4chan user.
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- NovelAI and KoboldAI presets: https://github.com/KoboldAI/KoboldAI-Client/wiki/Settings-Presets
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- Pygmalion preset, code for early stopping in chat mode, code for some of the sliders, --chat mode colors: https://github.com/PygmalionAI/gradio-ui/
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