| license: apache-2.0 | |
| library_name: diffusers | |
| pipeline_tag: text-to-image | |
| # Scale-wise Distillation 3.5 Large | |
| Scale-wise Distillation (SwD) is a novel framework for accelerating diffusion models (DMs) | |
| by progressively increasing spatial resolution during the generation process. | |
| <br>SwD achieves significant speedups (2.5× to 10×) compared to full-resolution models | |
| while maintaining or even improving image quality. | |
|  | |
| ## Usage | |
| To generate images using SwD, go to <a href="https://github.com/yandex-research/swd ">GitHub</a> | |
| or <a href="https://huggingface.co/spaces/dbaranchuk/Scale-wise-Distillation">Hugging Face's demo </a>. | |
| This is a Hugging Face Diffusers implementation of the paper [Scale-wise Distillation of Diffusion Models](https://huggingface.co/papers/2503.16397). | |
| The project page can be found at https://yandex-research.github.io/swd | |
| ## Citation | |
| ```bibtex | |
| @article{starodubcev2025swd, | |
| title={Scale-wise Distillation of Diffusion Models}, | |
| author={Nikita Starodubcev and Denis Kuznedelev and Artem Babenko and Dmitry Baranchuk}, | |
| journal={arXiv preprint arXiv:2503.16397}, | |
| year={2025} | |
| } | |
| ``` |