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| title: text-generation-webui | |
| app_file: server.py | |
| sdk: gradio | |
| sdk_version: 3.33.1 | |
| # Text generation web UI | |
| A gradio web UI for running Large Language Models like LLaMA, llama.cpp, GPT-J, Pythia, OPT, and GALACTICA. | |
| Its goal is to become the [AUTOMATIC1111/stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui) of text generation. | |
| | |  | | |
| |:---:|:---:| | |
| | |  | | |
| ## Features | |
| * 3 interface modes: default, notebook, and chat | |
| * Multiple model backends: tranformers, llama.cpp, AutoGPTQ, GPTQ-for-LLaMa, ExLlama, RWKV, FlexGen | |
| * Dropdown menu for quickly switching between different models | |
| * LoRA: load and unload LoRAs on the fly, load multiple LoRAs at the same time, train a new LoRA | |
| * Precise instruction templates for chat mode, including Alpaca, Vicuna, Open Assistant, Dolly, Koala, ChatGLM, MOSS, RWKV-Raven, Galactica, StableLM, WizardLM, Baize, Ziya, Chinese-Vicuna, MPT, INCITE, Wizard Mega, KoAlpaca, Vigogne, Bactrian, h2o, and OpenBuddy | |
| * [Multimodal pipelines, including LLaVA and MiniGPT-4](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/multimodal) | |
| * 8-bit and 4-bit inference through bitsandbytes | |
| * CPU mode for transformers models | |
| * [DeepSpeed ZeRO-3 inference](docs/DeepSpeed.md) | |
| * [Extensions](docs/Extensions.md) | |
| * [Custom chat characters](docs/Chat-mode.md) | |
| * Very efficient text streaming | |
| * Markdown output with LaTeX rendering, to use for instance with [GALACTICA](https://github.com/paperswithcode/galai) | |
| * Nice HTML output for GPT-4chan | |
| * API, including endpoints for websocket streaming ([see the examples](https://github.com/oobabooga/text-generation-webui/blob/main/api-examples)) | |
| To learn how to use the various features, check out the Documentation: https://github.com/oobabooga/text-generation-webui/tree/main/docs | |
| ## Installation | |
| ### One-click installers | |
| | Windows | Linux | macOS | WSL | | |
| |--------|--------|--------|--------| | |
| | [oobabooga-windows.zip](https://github.com/oobabooga/text-generation-webui/releases/download/installers/oobabooga_windows.zip) | [oobabooga-linux.zip](https://github.com/oobabooga/text-generation-webui/releases/download/installers/oobabooga_linux.zip) |[oobabooga-macos.zip](https://github.com/oobabooga/text-generation-webui/releases/download/installers/oobabooga_macos.zip) | [oobabooga-wsl.zip](https://github.com/oobabooga/text-generation-webui/releases/download/installers/oobabooga_wsl.zip) | | |
| Just download the zip above, extract it, and double-click on "start". The web UI and all its dependencies will be installed in the same folder. | |
| * The source codes are here: https://github.com/oobabooga/one-click-installers | |
| * There is no need to run the installers as admin. | |
| * AMD doesn't work on Windows. | |
| * Huge thanks to [@jllllll](https://github.com/jllllll), [@ClayShoaf](https://github.com/ClayShoaf), and [@xNul](https://github.com/xNul) for their contributions to these installers. | |
| ### Manual installation using Conda | |
| Recommended if you have some experience with the command line. | |
| #### 0. Install Conda | |
| https://docs.conda.io/en/latest/miniconda.html | |
| On Linux or WSL, it can be automatically installed with these two commands: | |
| ``` | |
| curl -sL "https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh" > "Miniconda3.sh" | |
| bash Miniconda3.sh | |
| ``` | |
| Source: https://educe-ubc.github.io/conda.html | |
| #### 1. Create a new conda environment | |
| ``` | |
| conda create -n textgen python=3.10.9 | |
| conda activate textgen | |
| ``` | |
| #### 2. Install Pytorch | |
| | System | GPU | Command | | |
| |--------|---------|---------| | |
| | Linux/WSL | NVIDIA | `pip3 install torch torchvision torchaudio` | | |
| | Linux | AMD | `pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm5.4.2` | | |
| | MacOS + MPS (untested) | Any | `pip3 install torch torchvision torchaudio` | | |
| | Windows | NVIDIA | `pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117` | | |
| The up-to-date commands can be found here: https://pytorch.org/get-started/locally/. | |
| #### 2.1 Special instructions | |
| * MacOS users: https://github.com/oobabooga/text-generation-webui/pull/393 | |
| * AMD users: https://rentry.org/eq3hg | |
| #### 3. Install the web UI | |
| ``` | |
| git clone https://github.com/oobabooga/text-generation-webui | |
| cd text-generation-webui | |
| pip install -r requirements.txt | |
| ``` | |
| #### bitsandbytes | |
| bitsandbytes >= 0.39 may not work on older NVIDIA GPUs. In that case, to use `--load-in-8bit`, you may have to downgrade like this: | |
| * Linux: `pip install bitsandbytes==0.38.1` | |
| * Windows: `pip install https://github.com/jllllll/bitsandbytes-windows-webui/raw/main/bitsandbytes-0.38.1-py3-none-any.whl` | |
| ### Alternative: Docker | |
| ``` | |
| ln -s docker/{Dockerfile,docker-compose.yml,.dockerignore} . | |
| cp docker/.env.example .env | |
| # Edit .env and set TORCH_CUDA_ARCH_LIST based on your GPU model | |
| docker compose up --build | |
| ``` | |
| * You need to have docker compose v2.17 or higher installed. See [this guide](https://github.com/oobabooga/text-generation-webui/blob/main/docs/Docker.md) for instructions. | |
| * For additional docker files, check out [this repository](https://github.com/Atinoda/text-generation-webui-docker). | |
| ### Updating the requirements | |
| From time to time, the `requirements.txt` changes. To update, use this command: | |
| ``` | |
| conda activate textgen | |
| cd text-generation-webui | |
| pip install -r requirements.txt --upgrade | |
| ``` | |
| ## Downloading models | |
| Models should be placed inside the `models/` folder. | |
| [Hugging Face](https://huggingface.co/models?pipeline_tag=text-generation&sort=downloads) is the main place to download models. These are some examples: | |
| * [Pythia](https://huggingface.co/models?sort=downloads&search=eleutherai%2Fpythia+deduped) | |
| * [OPT](https://huggingface.co/models?search=facebook/opt) | |
| * [GALACTICA](https://huggingface.co/models?search=facebook/galactica) | |
| * [GPT-J 6B](https://huggingface.co/EleutherAI/gpt-j-6B/tree/main) | |
| You can automatically download a model from HF using the script `download-model.py`: | |
| python download-model.py organization/model | |
| For example: | |
| python download-model.py facebook/opt-1.3b | |
| To download a protected model, set env vars `HF_USER` and `HF_PASS` to your Hugging Face username and password (or [User Access Token](https://huggingface.co/settings/tokens)). The model's terms must first be accepted on the HF website. | |
| #### GGML models | |
| You can drop these directly into the `models/` folder, making sure that the file name contains `ggml` somewhere and ends in `.bin`. | |
| #### GPT-4chan | |
| <details> | |
| <summary> | |
| Instructions | |
| </summary> | |
| [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: | |
| * Torrent: [16-bit](https://archive.org/details/gpt4chan_model_float16) / [32-bit](https://archive.org/details/gpt4chan_model) | |
| * Direct download: [16-bit](https://theswissbay.ch/pdf/_notpdf_/gpt4chan_model_float16/) / [32-bit](https://theswissbay.ch/pdf/_notpdf_/gpt4chan_model/) | |
| 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. | |
| After downloading the model, follow these steps: | |
| 1. Place the files under `models/gpt4chan_model_float16` or `models/gpt4chan_model`. | |
| 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). | |
| 3. Download GPT-J 6B's tokenizer files (they will be automatically detected when you attempt to load GPT-4chan): | |
| ``` | |
| python download-model.py EleutherAI/gpt-j-6B --text-only | |
| ``` | |
| When you load this model in default or notebook modes, the "HTML" tab will show the generated text in 4chan format. | |
| </details> | |
| ## Starting the web UI | |
| conda activate textgen | |
| cd text-generation-webui | |
| python server.py | |
| Then browse to | |
| `http://localhost:7860/?__theme=dark` | |
| Optionally, you can use the following command-line flags: | |
| #### Basic settings | |
| | Flag | Description | | |
| |--------------------------------------------|-------------| | |
| | `-h`, `--help` | Show this help message and exit. | | |
| | `--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. | | |
| | `--multi-user` | Multi-user mode. Chat histories are not saved or automatically loaded. WARNING: this is highly experimental. | | |
| | `--character CHARACTER` | The name of the character to load in chat mode by default. | | |
| | `--model MODEL` | Name of the model to load by default. | | |
| | `--lora LORA [LORA ...]` | The list of LoRAs to load. If you want to load more than one LoRA, write the names separated by spaces. | | |
| | `--model-dir MODEL_DIR` | Path to directory with all the models. | | |
| | `--lora-dir LORA_DIR` | Path to directory with all the loras. | | |
| | `--model-menu` | Show a model menu in the terminal when the web UI is first launched. | | |
| | `--no-stream` | Don't stream the text output in real time. | | |
| | `--settings SETTINGS_FILE` | Load the default interface settings from this yaml file. See `settings-template.yaml` for an example. If you create a file called `settings.yaml`, 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. | | |
| | `--verbose` | Print the prompts to the terminal. | | |
| #### Model loader | |
| | Flag | Description | | |
| |--------------------------------------------|-------------| | |
| | `--loader LOADER` | Choose the model loader manually, otherwise, it will get autodetected. Valid options: transformers, autogptq, gptq-for-llama, exllama, exllama_hf, llamacpp, rwkv, flexgen | | |
| #### Accelerate/transformers | |
| | Flag | Description | | |
| |---------------------------------------------|-------------| | |
| | `--cpu` | Use the CPU to generate text. Warning: Training on CPU is extremely slow.| | |
| | `--auto-devices` | Automatically split the model across the available GPU(s) and CPU. | | |
| | `--gpu-memory GPU_MEMORY [GPU_MEMORY ...]` | Maximum GPU memory in GiB to be allocated per GPU. Example: `--gpu-memory 10` for a single GPU, `--gpu-memory 10 5` for two GPUs. You can also set values in MiB like `--gpu-memory 3500MiB`. | | |
| | `--cpu-memory CPU_MEMORY` | Maximum CPU memory in GiB to allocate for offloaded weights. Same as above.| | |
| | `--disk` | If the model is too large for your GPU(s) and CPU combined, send the remaining layers to the disk. | | |
| | `--disk-cache-dir DISK_CACHE_DIR` | Directory to save the disk cache to. Defaults to `cache/`. | | |
| | `--load-in-8bit` | Load the model with 8-bit precision (using bitsandbytes).| | |
| | `--bf16` | Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU. | | |
| | `--no-cache` | Set `use_cache` to False while generating text. This reduces the VRAM usage a bit with a performance cost. | | |
| | `--xformers` | Use xformer's memory efficient attention. This should increase your tokens/s. | | |
| | `--sdp-attention` | Use torch 2.0's sdp attention. | | |
| | `--trust-remote-code` | Set trust_remote_code=True while loading a model. Necessary for ChatGLM and Falcon. | | |
| #### Accelerate 4-bit | |
| ⚠️ Requires minimum compute of 7.0 on Windows at the moment. | |
| | Flag | Description | | |
| |---------------------------------------------|-------------| | |
| | `--load-in-4bit` | Load the model with 4-bit precision (using bitsandbytes). | | |
| | `--compute_dtype COMPUTE_DTYPE` | compute dtype for 4-bit. Valid options: bfloat16, float16, float32. | | |
| | `--quant_type QUANT_TYPE` | quant_type for 4-bit. Valid options: nf4, fp4. | | |
| | `--use_double_quant` | use_double_quant for 4-bit. | | |
| #### llama.cpp | |
| | Flag | Description | | |
| |-------------|-------------| | |
| | `--threads` | Number of threads to use. | | |
| | `--n_batch` | Maximum number of prompt tokens to batch together when calling llama_eval. | | |
| | `--no-mmap` | Prevent mmap from being used. | | |
| | `--mlock` | Force the system to keep the model in RAM. | | |
| | `--cache-capacity CACHE_CAPACITY` | Maximum cache capacity. Examples: 2000MiB, 2GiB. When provided without units, bytes will be assumed. | | |
| | `--n-gpu-layers N_GPU_LAYERS` | Number of layers to offload to the GPU. Only works if llama-cpp-python was compiled with BLAS. Set this to 1000000000 to offload all layers to the GPU. | | |
| | `--n_ctx N_CTX` | Size of the prompt context. | | |
| | `--llama_cpp_seed SEED` | Seed for llama-cpp models. Default 0 (random). | | |
| #### AutoGPTQ | |
| | Flag | Description | | |
| |------------------|-------------| | |
| | `--triton` | Use triton. | | |
| | `--no_inject_fused_attention` | Disable the use of fused attention, which will use less VRAM at the cost of slower inference. | | |
| | `--no_inject_fused_mlp` | Triton mode only: disable the use of fused MLP, which will use less VRAM at the cost of slower inference. | | |
| | `--no_use_cuda_fp16` | This can make models faster on some systems. | | |
| | `--desc_act` | For models that don't have a quantize_config.json, this parameter is used to define whether to set desc_act or not in BaseQuantizeConfig. | | |
| #### ExLlama | |
| | Flag | Description | | |
| |------------------|-------------| | |
| |`--gpu-split` | Comma-separated list of VRAM (in GB) to use per GPU device for model layers, e.g. `20,7,7` | | |
| |`--max_seq_len MAX_SEQ_LEN` | Maximum sequence length. | | |
| |`--compress_pos_emb COMPRESS_POS_EMB` | Positional embeddings compression factor. Should typically be set to max_seq_len / 2048. | | |
| |`--alpha_value ALPHA_VALUE` | Positional embeddings alpha factor for NTK RoPE scaling. Same as above. Use either this or compress_pos_emb, not both. ` | |
| #### GPTQ-for-LLaMa | |
| | Flag | Description | | |
| |---------------------------|-------------| | |
| | `--wbits WBITS` | Load a pre-quantized model with specified precision in bits. 2, 3, 4 and 8 are supported. | | |
| | `--model_type MODEL_TYPE` | Model type of pre-quantized model. Currently LLaMA, OPT, and GPT-J are supported. | | |
| | `--groupsize GROUPSIZE` | Group size. | | |
| | `--pre_layer PRE_LAYER [PRE_LAYER ...]` | The number of layers to allocate to the GPU. Setting this parameter enables CPU offloading for 4-bit models. For multi-gpu, write the numbers separated by spaces, eg `--pre_layer 30 60`. | | |
| | `--checkpoint CHECKPOINT` | The path to the quantized checkpoint file. If not specified, it will be automatically detected. | | |
| | `--monkey-patch` | Apply the monkey patch for using LoRAs with quantized models. | |
| | `--quant_attn` | (triton) Enable quant attention. | | |
| | `--warmup_autotune` | (triton) Enable warmup autotune. | | |
| | `--fused_mlp` | (triton) Enable fused mlp. | | |
| #### FlexGen | |
| | Flag | Description | | |
| |------------------|-------------| | |
| | `--percent PERCENT [PERCENT ...]` | FlexGen: allocation percentages. Must be 6 numbers separated by spaces (default: 0, 100, 100, 0, 100, 0). | | |
| | `--compress-weight` | FlexGen: Whether to compress weight (default: False).| | |
| | `--pin-weight [PIN_WEIGHT]` | FlexGen: whether to pin weights (setting this to False reduces CPU memory by 20%). | | |
| #### DeepSpeed | |
| | Flag | Description | | |
| |---------------------------------------|-------------| | |
| | `--deepspeed` | Enable the use of DeepSpeed ZeRO-3 for inference via the Transformers integration. | | |
| | `--nvme-offload-dir NVME_OFFLOAD_DIR` | DeepSpeed: Directory to use for ZeRO-3 NVME offloading. | | |
| | `--local_rank LOCAL_RANK` | DeepSpeed: Optional argument for distributed setups. | | |
| #### RWKV | |
| | Flag | Description | | |
| |---------------------------------|-------------| | |
| | `--rwkv-strategy RWKV_STRATEGY` | RWKV: The strategy to use while loading the model. Examples: "cpu fp32", "cuda fp16", "cuda fp16i8". | | |
| | `--rwkv-cuda-on` | RWKV: Compile the CUDA kernel for better performance. | | |
| #### Gradio | |
| | Flag | Description | | |
| |---------------------------------------|-------------| | |
| | `--listen` | Make the web UI reachable from your local network. | | |
| | `--listen-host LISTEN_HOST` | The hostname that the server will use. | | |
| | `--listen-port LISTEN_PORT` | The listening port that the server will use. | | |
| | `--share` | Create a public URL. This is useful for running the web UI on Google Colab or similar. | | |
| | `--auto-launch` | Open the web UI in the default browser upon launch. | | |
| | `--gradio-auth USER:PWD` | set gradio authentication like "username:password"; or comma-delimit multiple like "u1:p1,u2:p2,u3:p3" | | |
| | `--gradio-auth-path GRADIO_AUTH_PATH` | Set the gradio authentication file path. The file should contain one or more user:password pairs in this format: "u1:p1,u2:p2,u3:p3" | | |
| #### API | |
| | Flag | Description | | |
| |---------------------------------------|-------------| | |
| | `--api` | Enable the API extension. | | |
| | `--public-api` | Create a public URL for the API using Cloudfare. | | |
| | `--api-blocking-port BLOCKING_PORT` | The listening port for the blocking API. | | |
| | `--api-streaming-port STREAMING_PORT` | The listening port for the streaming API. | | |
| #### Multimodal | |
| | Flag | Description | | |
| |---------------------------------------|-------------| | |
| | `--multimodal-pipeline PIPELINE` | The multimodal pipeline to use. Examples: `llava-7b`, `llava-13b`. | | |
| Out of memory errors? [Check the low VRAM guide](docs/Low-VRAM-guide.md). | |
| ## Presets | |
| Inference settings presets can be created under `presets/` as yaml files. These files are detected automatically at startup. | |
| The presets that are included by default are the result of a contest that received 7215 votes. More details can be found [here](https://github.com/oobabooga/oobabooga.github.io/blob/main/arena/results.md). | |
| ## Contributing | |
| * Pull requests, suggestions, and issue reports are welcome. | |
| * Make sure to carefully [search](https://github.com/oobabooga/text-generation-webui/issues) existing issues before starting a new one. | |
| * If you have some experience with git, testing an open pull request and leaving a comment on whether it works as expected or not is immensely helpful. | |
| * A simple way to contribute, even if you are not a programmer, is to leave a 👍 on an issue or pull request that you find relevant. | |
| ## Community | |
| * Subreddit: https://www.reddit.com/r/oobaboogazz/ | |
| * Discord: https://discord.gg/jwZCF2dPQN | |
| ## Credits | |
| - Gradio dropdown menu refresh button, code for reloading the interface: https://github.com/AUTOMATIC1111/stable-diffusion-webui | |
| - Godlike preset: https://github.com/KoboldAI/KoboldAI-Client/wiki/Settings-Presets | |
| - Code for some of the sliders: https://github.com/PygmalionAI/gradio-ui/ | |