---
license: apache-2.0
datasets:
- ILSVRC/imagenet-1k
library_name: diffusers
---
# pi-Flow: Policy-Based Flow Models
Distilled 1-step and 2-step ImageNet DiTs proposed in the paper:
**pi-Flow: Policy-Based Few-Step Generation via Imitation Distillation**
[Hansheng Chen](https://lakonik.github.io/)1,
[Kai Zhang](https://kai-46.github.io/website/)2,
[Hao Tan](https://research.adobe.com/person/hao-tan/)2,
[Leonidas Guibas](https://geometry.stanford.edu/?member=guibas)1,
[Gordon Wetzstein](http://web.stanford.edu/~gordonwz/)1,
[Sai Bi](https://sai-bi.github.io/)2
1Stanford University, 2Adobe Research
[[arXiv](https://arxiv.org/abs/2510.14974)] [[Code](https://github.com/Lakonik/piFlow)] [[pi-Qwen Demo🤗](https://huggingface.co/spaces/Lakonik/pi-Qwen)] [[pi-FLUX Demo🤗](https://huggingface.co/spaces/Lakonik/pi-FLUX.1)]

## Citation
```
@misc{piflow,
title={pi-Flow: Policy-Based Few-Step Generation via Imitation Distillation},
author={Hansheng Chen and Kai Zhang and Hao Tan and Leonidas Guibas and Gordon Wetzstein and Sai Bi},
year={2025},
eprint={2510.14974},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/2510.14974},
}
```