speedup-plugin-for-stable-diffusions

This repo is the official implementation of SpeedUpNet(SUN) in PyTorch.

Paper: SpeedUpNet: A Plug-and-Play Hyper-Network for Accelerating Text-to-Image Diffusion Models

10x speed up on stable diffusions

Introducing SUN as a plug-in, a pre-trained SD can generate high-quality images in only 4 steps. We can test on MacBook Pro(M1 Pro):

DPM-Solver++ 20 steps, 16 seconds (baseline)

+SUN, 4 steps, 2 seconds

See more on our webpage

Realtime Controllable Generation

SUN is compatible with controllable tools. Real-time rendering can be achieved on high-end consumer-grade graphics cards.

Usage

cd demo

# prepare models

python controlnet_lora.py

Download SUN adapter

https://huggingface.co/Williechai/SpeedUpNet/tree/main

Update

2023.12.15: Readme.

Citation

If you find this work is helpful in your research, please cite our work:

@misc{chai2023speedupnet,
      title={SpeedUpNet: A Plug-and-Play Hyper-Network for Accelerating Text-to-Image Diffusion Models}, 
      author={Weilong Chai and DanDan Zheng and Jiajiong Cao and Zhiquan Chen and Changbao Wang and Chenguang Ma},
      year={2023},
      eprint={2312.08887},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

Contact

If you have any questions, feel free to open an issue or directly contact me via: weilong.cwl@antgroup.com.

williechai/speedup-plugin-for-stable-diffusions