Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.


Docker image build Run examples

OneDiff is an out-of-the-box acceleration library for diffusion models, it provides:

OneDiff is the abbreviation of "one line of code to accelerate diffusion models". Here is the latested news:

The Full introduction of OneDiff:

More About OneDiff

State-of-the-art performance

SDXL E2E time

  • Model stabilityai/stable-diffusion-xl-base-1.0;
  • Image size 1024*1024, batch size 1, steps 30;
  • NVIDIA A100 80G SXM4;

SVD E2E time

  • Model stabilityai/stable-video-diffusion-img2vid-xt;
  • Image size 576*1024, batch size 1, steps 25, decoder chunk size 5;
  • NVIDIA A100 80G SXM4;

Acceleration for State-of-the-art models

OneDiff support the acceleratioin for SOTA models.

AIGC Type Models HF diffusers ComfyUI SD web UI
Community Enterprise Community Enterprise Community Enterprise
Image SD 1.5 stable stable stable stable beta beta
SD 2.1 stable stable stable stable beta beta
SDXL stable stable stable stable beta beta
LoRA stable stable beta
ControlNet stable stable
SDXL Turbo stable stable
LCM stable stable
SDXL DeepCache stable beta stable beta
InstantID stable stable
Video SVD(stable Video Diffusion) stable beta stable beta
SVD DeepCache stable beta stable beta

Note: Enterprise Edition contains all the functionality in Community Edition.

  • stable: release for public usage, and has long-term support;
  • beta: release for professional usage, and has long-term support;
  • alpha: early release for expert usage, and is under active development;

Acceleration for production

PyTorch Module compilation

Avoid compilation time for new input shape

Avoid compilation time for online serving

Compile and save the compiled result offline, then load it online for serving

OneDiff Enterprise Edition

If you need Enterprise-level Support for your system or business, you can

OneDiff Enterprise Edition can be subscripted for one month and one GPU and the cost is low.

  OneDiff Enterprise OneDiff Community
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 experimental technology/feature Yes

Roadmap

OneDiff Development Roadmap

Community and Support

Installation

OS and GPU support

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

OneDiff Installation

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

NOTE: If you intend to utilize plugins for ComfyUI/StableDiffusion-WebUI, we highly recommend installing OneDiff from the source rather than PyPI. This is necessary as you'll need to manually copy (or create a soft link) for the relevant code into the extension folder of these UIs/Libs.

4. (Optional)Login huggingface-cli

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

Release

  • run examples to check it works

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

    .github/workflows/pub.yml
    src/onediff/__init__.py
    
  • install build package

    python3 -m pip install build
    
  • build wheel

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

    twine upload dist/*
    

Metadata

Release files for onediff 0.12.1.dev202403020122

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for onediff 0.12.1.dev202403020122
File Size Uploaded
onediff-0.12.1.dev202403020122.tar.gz 68.6 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for onediff 0.12.1.dev202403020122
File Interpreter ABI Platform
onediff-0.12.1.dev202403020122-py3-none-any.whl Python 3 none any Details

Total release size: 145.9 kB

Release files / onediff-0.12.1.dev202403020122.tar.gz

Download URL onediff-0.12.1.dev202403020122.tar.gz
Size 68.6 kB
Tags Source
SHA-256 checksum
How to use checksums
e7e4a337b0b56f39973e48d14d4dafd436115ab8e9bf29693373e079ce9d27ef
BLAKE2b-256 checksum
How to use checksums
72775a74a30c1ab68bc618f595b43c8146a256e953a074e70de3f0b79cdc35b6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.9.18

Release files / onediff-0.12.1.dev202403020122-py3-none-any.whl

Download URL onediff-0.12.1.dev202403020122-py3-none-any.whl
Size 77.3 kB
Tags Python 3
SHA-256 checksum
How to use checksums
d6f3c5bd02938491d2afe2e0b9c78f65fb05decce49d6c09421c60ea634efc6f
BLAKE2b-256 checksum
How to use checksums
39637bb5d98c9d29de4e68b3e1035388c12d0183520fccfb334dc567e4d4f282
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.9.18

Release history Release notifications | RSS feed

1.2.0

2 release files

1.1.0

2 release files

1.0.0

2 release files

This release

0.11.4

1 release file

0.10.0

1 release file

0.9.0

1 release file

0.8.0

1 release file

0.7.0

1 release file

0.6.0

1 release file

0.5.0

1 release file

0.4.0

1 release file

0.3.0

1 release file

0.2.0

1 release file

0.1.0

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page