---
license: other
license_name: anyflow-wan-non-commercial
license_link: https://huggingface.co/nvidia/AnyFlow-Wan2.1-T2V-1.3B-Diffusers
base_model: nvidia/AnyFlow-Wan2.1-T2V-1.3B-Diffusers
pipeline_tag: text-to-video
library_name: diffusers
tags:
- lora
- reinforcement-learning
- few-step
- flow-map
- fewsteprl
---

# FewStepRL — Wan2.1-T2V-1.3B checkpoints

Released checkpoints of **FewStepRL: Fine-tuning Few-step Diffusion Models with Reinforcement Learning**
(video experiments, 4-step AnyFlow-Wan2.1-T2V-1.3B flow map, 480×832, 81 frames).

[Paper (arXiv:2611.08240)](https://arxiv.org/abs/2611.08240) ·
[Code](https://github.com/EDAPINENUT/fewsteprl-wan21) ·
[Project page](https://edapinenut.github.io/fewsteprl.page/) ·
[Image checkpoints (SD3.5)](https://huggingface.co/Delcher/fewsteprl-sd35)

## Contents

```
<trial>/
  config.yaml                         # the config the run saved
  checkpoint-250/generator_ema.pt     # EMA generator: LoRA A/B + condition_embedder.delta_embedder
SHA256SUMS
```

| trial | trainer | step |
|---|---|---|
| meanflownft | `meanflow_nft` | 250 |
| dmdnft | `dmdnft_rl` | 250 |
| dmdawm | `dmdawm_rl` | 250 |
| fewstepgrpo | `meanflowgrpo_rl` | 250 |
| meanflowawm | `meanflowawm_rl` | 250 |
| meanflowopsd | `meanflowopsd_rl` | 250 |
| reflmx | `meanflowrefl_rl` | 250 |

All trials share the reward HPSv3 general + HPSv3 percentile + VideoAlign MQ + VideoAlign TA. Scores (training
reward and VBench): [checkpoints/README.md](https://github.com/EDAPINENUT/fewsteprl-wan21/blob/main/checkpoints/README.md).

## Usage

Download the weights into the `checkpoints/` directory of the code repository:

```bash
git clone https://github.com/EDAPINENUT/fewsteprl-wan21 && cd fewsteprl-wan21
bash download_scripts/download_assets.sh          # AnyFlow-Wan, reward models, VBench weights
hf download Delcher/fewsteprl-wan21 --local-dir checkpoints --include "*.pt"
cd checkpoints && shasum -a 256 -c SHA256SUMS && cd ..
```

`generator_ema.pt` is applied on top of the full AnyFlow-Wan2.1-T2V-1.3B pipeline:

```bash
python inference.py scripts/eval/configs/sample_wan.yaml --prompt "..." \
  --override seed=0 mode=meanflow_nft meanflow_nft_path=checkpoints/dmdnft/checkpoint-250/generator_ema.pt
bash scripts/eval/eval_ckpt.sh dmdnft 8           # training rewards on the 256 test prompts
```

## License

The weights are derivatives of
[nvidia/AnyFlow-Wan2.1-T2V-1.3B-Diffusers](https://huggingface.co/nvidia/AnyFlow-Wan2.1-T2V-1.3B-Diffusers),
whose license restricts the model and derivative weights to **non-commercial use**.

## Citation

```bibtex
@article{lin2026fewsteprl,
  title   = {FewStepRL: Fine-tuning Few-step Diffusion Models with Reinforcement Learning},
  author  = {Lin, Haitao and Ren, Minsi and Li, Yang and Ge, Xingtong and
             Hu, Zheyuan and Hu, Peiyan and Wu, Tailin},
  journal = {arXiv preprint arXiv:2611.08240},
  year    = {2026}
}
```