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yaoshining commited on Jul 3, 2023

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-# 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.
-|![Image1](https://github.com/oobabooga/screenshots/raw/main/qa.png) | ![Image2](https://github.com/oobabooga/screenshots/raw/main/cai3.png) |
-|:---:|:---:|
-|![Image3](https://github.com/oobabooga/screenshots/raw/main/gpt4chan.png) | ![Image4](https://github.com/oobabooga/screenshots/raw/main/galactica.png) |
-## 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
-```
-#### llama.cpp with GPU acceleration
-Requires the additional compilation step described here: [GPU acceleration](https://github.com/oobabooga/text-generation-webui/blob/main/docs/llama.cpp-models.md#gpu-acceleration).
-#### 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. |
-| `--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. |
-#### 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/

+---
+title: Text Generation Webui
+emoji: 👀
+colorFrom: green
+colorTo: red
+sdk: gradio
+sdk_version: 3.35.2
+app_file: app.py
+pinned: false
+license: apache-2.0
+---
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference