Spaces:
Runtime error
Runtime error
license: openrail | |
title: SinGPT Premium | |
sdk: gradio | |
emoji: π | |
colorFrom: red | |
colorTo: blue | |
app_file: run.py | |
# 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 | |
* Dropdown menu for switching between models | |
* Notebook mode that resembles OpenAI's playground | |
* Chat mode for conversation and role-playing | |
* Instruct mode compatible with various formats, including Alpaca, Vicuna, Open Assistant, Dolly, Koala, ChatGLM, MOSS, RWKV-Raven, Galactica, StableLM, WizardLM, Baize, MPT, and INCITE | |
* [Multimodal pipelines, including LLaVA and MiniGPT-4](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/multimodal) | |
* Markdown output for [GALACTICA](https://github.com/paperswithcode/galai), including LaTeX rendering | |
* Nice HTML output for GPT-4chan | |
* [Custom chat characters](docs/Chat-mode.md) | |
* Advanced chat features (send images, get audio responses with TTS) | |
* Very efficient text streaming | |
* Parameter presets | |
* [LLaMA model](docs/LLaMA-model.md) | |
* [4-bit GPTQ mode](docs/GPTQ-models-(4-bit-mode).md) | |
* [LoRA (loading and training)](docs/Using-LoRAs.md) | |
* [llama.cpp](docs/llama.cpp-models.md) | |
* [RWKV model](docs/RWKV-model.md) | |
* 8-bit mode | |
* Layers splitting across GPU(s), CPU, and disk | |
* CPU mode | |
* [FlexGen](docs/FlexGen.md) | |
* [DeepSpeed ZeRO-3](docs/DeepSpeed.md) | |
* API [with](https://github.com/oobabooga/text-generation-webui/blob/main/api-example-stream.py) streaming and [without](https://github.com/oobabooga/text-generation-webui/blob/main/api-example.py) streaming | |
* [Extensions](docs/Extensions.md) - see the [user extensions list](https://github.com/oobabooga/text-generation-webui-extensions) | |
## Installation | |
### One-click installers | |
| Windows | Linux | macOS | | |
|-------|--------|--------| | |
| [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) | | |
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. | |
On Windows, I additionally recommend carrying out the installation on WSL instead of the base system: [WSL installation guide](https://github.com/oobabooga/text-generation-webui/blob/main/docs/WSL-installation-guide.md). | |
#### 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` | | |
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 | |
``` | |
#### 4. Install GPTQ-for-LLaMa and the monkey patch | |
The base installation covers [transformers](https://github.com/huggingface/transformers) models (`AutoModelForCausalLM` and `AutoModelForSeq2SeqLM` specifically) and [llama.cpp](https://github.com/ggerganov/llama.cpp) (GGML) models. | |
To use 4-bit GPU models, the additional installation steps below are necessary: | |
[GPTQ models (4 bit mode)](https://github.com/oobabooga/text-generation-webui/blob/main/docs/GPTQ-models-(4-bit-mode).md) | |
### Alternative: manual Windows installation | |
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: [Windows installation guide](https://github.com/oobabooga/text-generation-webui/blob/main/docs/Windows-installation-guide.md). | |
### 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 in your system. To see how to install docker compose itself, see the guide in [here](https://github.com/oobabooga/text-generation-webui/blob/main/docs/Docker.md). | |
Contributed by [@loeken](https://github.com/loeken) in [#633](https://github.com/oobabooga/text-generation-webui/pull/633) | |
### 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 | |
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. | |
#### 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 | |
[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 | |
``` | |
## 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 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. | | |
| `--verbose` | Print the prompts to the terminal. | | |
#### 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 ...]` | 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. 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.| | |
| `--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. | | |
#### 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. | | |
#### GPTQ | |
| 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 | | |
|------------------|-------------| | |
| `--flexgen` | Enable the use of FlexGen offloading. | | |
| `--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-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. | | |
#### 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 text files. These files are detected automatically at startup. | |
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. | |
[Visualization](https://user-images.githubusercontent.com/112222186/228956352-1addbdb9-2456-465a-b51d-089f462cd385.png) | |
## Documentation | |
Make sure to check out the documentation for an in-depth guide on how to use the web UI. | |
https://github.com/oobabooga/text-generation-webui/tree/main/docs | |
## Contributing | |
Pull requests, suggestions, and issue reports are welcome. | |
You are also welcome to review open pull requests. | |
Before reporting a bug, make sure that you have: | |
1. Created a conda environment and installed the dependencies exactly as in the *Installation* section above. | |
2. [Searched](https://github.com/oobabooga/text-generation-webui/issues) to see if an issue already exists for the issue you encountered. | |
## Credits | |
- Gradio dropdown menu refresh button, code for reloading the interface: https://github.com/AUTOMATIC1111/stable-diffusion-webui | |
- Verbose preset: Anonymous 4chan user. | |
- NovelAI and KoboldAI presets: https://github.com/KoboldAI/KoboldAI-Client/wiki/Settings-Presets | |
- Code for early stopping in chat mode, code for some of the sliders: https://github.com/PygmalionAI/gradio-ui/ |