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an out-of-the-box acceleration library for diffusion models

Project description


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OneDiff is an out-of-the-box acceleration library for diffusion models (especially for ComfyUI, HF diffusers, and Stable Diffusion web UI).

OneDiff is the abbreviation of "one line of code to accelerate diffusion models".

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Easy to use

State-of-the-art performance

OS and GPU support

  • Linux
    • If you want to use OneDiff on Windows, please use it under WSL.
  • NVIDIA GPUs

OneDiff Enterprise Edition

If you need Enterprise-level Support for your system or business, please send an email to contact@siliconflow.com and tell us about your user case, deployment scale, and requirements.

OneDiff Enterprise Edition can be subscripted for one month and one GPU and the cost is low: https://siliconflow.com/onediff.html

  OneDiff Enterprise OneDiff Community
SD/SDXL series model Optimization Yes Yes
UNet/VAE/ControlNet Optimization Yes Yes
LoRA(and dynamic switching LoRA) Yes Yes
SDXL Turbo/LCM Yes Yes
Stable Video Diffusion Yes Yes
HF diffusers Yes Yes
ComfyUI Yes Yes
Stable Diffusion web UI Yes Yes
Multiple Resolutions Yes(No time cost for most of the cases) Yes(No time cost for most of the cases)
More Extreme and Dedicated optimization(usually another 20~100% performance gain) Yes
Technical Support for deployment High priority support Community
Get the latest technology/feature Yes

Install from source or Using in Docker

Install from source

1. Install OneFlow

NOTE: We have updated OneFlow a lot for OneDiff, so please install OneFlow by the links below.

  • CUDA 11.8

    # For NA/EU users
    python3 -m pip install -U --pre oneflow -f https://github.com/siliconflow/oneflow_releases/releases/expanded_assets/community_cu118
    
    # For CN users
    python3 -m pip install --pre oneflow -f https://oneflow-pro.oss-cn-beijing.aliyuncs.com/branch/community/cu118
    
Click to get OneFlow packages for other CUDA versions.
  • CUDA 12.1

    # For NA/EU users
    python3 -m pip install -U --pre oneflow -f https://github.com/siliconflow/oneflow_releases/releases/expanded_assets/community_cu121
    
    # For CN users
    python3 -m pip install --pre oneflow -f https://oneflow-pro.oss-cn-beijing.aliyuncs.com/branch/community/cu121
    
  • CUDA 12.2

    # For NA/EU users
    python3 -m pip install -U --pre oneflow -f https://github.com/siliconflow/oneflow_releases/releases/expanded_assets/community_cu122
    
    # For CN users
    python3 -m pip install --pre oneflow -f https://oneflow-pro.oss-cn-beijing.aliyuncs.com/branch/community/cu122
    

2. Install torch and diffusers

python3 -m pip install "torch" "transformers==4.27.1" "diffusers[torch]==0.19.3"

3. Install OneDiff

  • From PyPI
pip install --pre onediff
  • From source
git clone https://github.com/siliconflow/onediff.git
cd onediff && python3 -m pip install -e .

4. (Optional)Login huggingface-cli

python3 -m pip install huggingface_hub
 ~/.local/bin/huggingface-cli login

Docker

docker pull oneflowinc/onediff:20231106

Release

  • run examples to check it works

    python3 examples/text_to_image.py
    python3 examples/text_to_image_dpmsolver.py
    
  • bump version in these files:

    src/onediff/__init__.py
    
  • install build package (optional)

    python3 -m pip install build
    
  • build wheel

    rm -rf dist
    python3 -m build
    
  • upload to pypi

    twine upload dist/*
    

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