cjwbw / hyper-sdxl-1step-t2i

Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

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Run time and cost

This model costs approximately $0.042 to run on Replicate, or 23 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia L40S GPU hardware. Predictions typically complete within 44 seconds. The predict time for this model varies significantly based on the inputs.

Readme

Hyper-SD

Official Repository of the paper: Hyper-SD.

Project Page: https://hyper-sd.github.io/

Citation

@misc{ren2024hypersd,
      title={Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis}, 
      author={Yuxi Ren and Xin Xia and Yanzuo Lu and Jiacheng Zhang and Jie Wu and Pan Xie and Xing Wang and Xuefeng Xiao},
      year={2024},
      eprint={2404.13686},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}