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@ -10,27 +10,30 @@ Its goal is to become the [AUTOMATIC1111/stable-diffusion-webui](https://github.
## Features
* 3 interface modes: default (two columns), notebook, and chat.
* Multiple model backends: [Transformers](https://github.com/huggingface/transformers), [llama.cpp](https://github.com/ggerganov/llama.cpp) (through [llama-cpp-python](https://github.com/abetlen/llama-cpp-python)), [ExLlamaV2](https://github.com/turboderp/exllamav2), [AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ), [AutoAWQ](https://github.com/casper-hansen/AutoAWQ), [TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM).
* Dropdown menu for quickly switching between different models.
* Large number of extensions (built-in and user-contributed), including Coqui TTS for realistic voice outputs, Whisper STT for voice inputs, translation, [multimodal pipelines](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/multimodal), vector databases, Stable Diffusion integration, and a lot more. See [the wiki](https://github.com/oobabooga/text-generation-webui/wiki/07-%E2%80%90-Extensions) and [the extensions directory](https://github.com/oobabooga/text-generation-webui-extensions) for details.
* [Chat with custom characters](https://github.com/oobabooga/text-generation-webui/wiki/03-%E2%80%90-Parameters-Tab#character).
* Precise chat templates for instruction-following models, including Llama-2-chat, Alpaca, Vicuna, Mistral.
* LoRA: train new LoRAs with your own data, load/unload LoRAs on the fly for generation.
* Transformers library integration: load models in 4-bit or 8-bit precision through bitsandbytes, use llama.cpp with transformers samplers (`llamacpp_HF` loader), CPU inference in 32-bit precision using PyTorch.
* Multiple backends for text generation in a single UI and API, including [Transformers](https://github.com/huggingface/transformers), [llama.cpp](https://github.com/ggerganov/llama.cpp) (through [llama-cpp-python](https://github.com/abetlen/llama-cpp-python)), [ExLlamaV2](https://github.com/turboderp/exllamav2), [AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ), [AutoAWQ](https://github.com/casper-hansen/AutoAWQ), and [TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM).
* OpenAI-compatible API server with Chat and Completions endpoints -- see the [examples](https://github.com/oobabooga/text-generation-webui/wiki/12-%E2%80%90-OpenAI-API#examples).
* Automatic prompt formatting for each model using the Jinja2 template in its metadata, ensuring high-quality outputs without manual intervention.
* Three chat modes: `instruct`, `chat-instruct`, and `chat`, allowing for both task-based interactions and casual conversations with characters.
* High-quality outputs in chat scenarios with the `chat-instruct` mode, which uses the model's template automatically.
* Easy switching between conversations and starting new ones through the "Past chats" menu in the main interface tab.
* Flexible text generation through autocompletion in the Default/Notebook tabs without being limited to chat turns. Send formatted chat conversations from the Chat tab to these tabs.
* Multiple sampling parameters and options for sophisticated text generation control.
* Quick downloading and loading of new models through the interface without restarting, using the "Model" tab.
* Simple LoRA fine-tuning tool to customize models with your data.
* Self-contained dependencies in the `installer_files` folder, avoiding interference with the system's Python environment. Precompiled Python wheels for the backends are in the `requirements.txt` and are transparently compiled using GitHub Actions.
* Extensions support, including numerous built-in and user-contributed extensions. See [the wiki](https://github.com/oobabooga/text-generation-webui/wiki/07-%E2%80%90-Extensions) and [the extensions directory](https://github.com/oobabooga/text-generation-webui-extensions) for details.
## How to install
1) Clone or [download](https://github.com/oobabooga/text-generation-webui/archive/refs/heads/main.zip) the repository.
2) Run the `start_linux.sh`, `start_windows.bat`, `start_macos.sh`, or `start_wsl.bat` script depending on your OS.
3) Select your GPU vendor when asked.
4) Once the installation ends, browse to `http://localhost:7860/?__theme=dark`.
4) Once the installation ends, browse to `http://localhost:7860`.
5) Have fun!
To restart the web UI in the future, just run the `start_` script again. This script creates an `installer_files` folder where it sets up the project's requirements. In case you need to reinstall the requirements, you can simply delete that folder and start the web UI again.
To restart the web UI in the future, just run the `start_` script again. This script creates an `installer_files` folder where it sets up the project's requirements. If you need to reinstall the requirements, you can simply delete that folder and start the web UI again.
The script accepts command-line flags. Alternatively, you can edit the `CMD_FLAGS.txt` file with a text editor and add your flags there.
The script accepts command-line flags. Alternatively, you can edit the `CMD_FLAGS.txt` file with a text editor and add your flags there, such as `--api` in case you need to use the API.
To get updates in the future, run `update_wizard_linux.sh`, `update_wizard_windows.bat`, `update_wizard_macos.sh`, or `update_wizard_wsl.bat`.