* 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)).
* 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.
* Windows: using conda on WSL ([WSL installation guide](https://github.com/oobabooga/text-generation-webui/wiki/Windows-Subsystem-for-Linux-(Ubuntu)-Installation-Guide)).
Conda can be downloaded here: https://docs.conda.io/en/latest/miniconda.html
If you experience bitsandbytes issues on WSL while trying to use `--load-in-8bit`, see this thread: https://github.com/microsoft/WSL/issues/5548#issuecomment-1292858815
As an alternative to the recommended WSL method, you can install the web UI natively on Windows using this guide. It will be a lot harder and the performance may be slower: [Installation instructions for human beings](https://github.com/oobabooga/text-generation-webui/wiki/Installation-instructions-for-human-beings).
This method lags behind the newest developments and does not support 8-bit mode on Windows without additional set up: https://github.com/oobabooga/text-generation-webui/issues/147#issuecomment-1456040134, https://github.com/oobabooga/text-generation-webui/issues/20#issuecomment-1411650652
[Hugging Face](https://huggingface.co/models?pipeline_tag=text-generation&sort=downloads) is the main place to download models. These are some noteworthy examples:
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.
[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:
| `-h`, `--help` | show this help message and exit |
| `--model MODEL` | Name of the model to load by default. |
| `--lora LORA` | Name of the LoRA to apply to the model 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.|
| `--load-in-4bit` | DEPRECATED: use `--gptq-bits 4` instead. |
| `--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. |
| `--gptq-model-type MODEL_TYPE` | Model type of pre-quantized model. Currently only LLaMa and OPT are supported. |
| `--bf16` | Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU. |
| `--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. |
| `--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.|
| `--extensions EXTENSIONS [EXTENSIONS ...]` | The list of extensions to load. If you want to load more than one extension, write the names separated by spaces. |
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.
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.
