---
license: mit
base_model:
- Wan-AI/Wan2.1-T2V-14B-Diffusers
- hunyuanvideo-community/HunyuanVideo
pipeline_tag: text-to-video
library_name: diffusers
---

# VORTA: Efficient Video Diffusion via Routing Sparse Attention

> TL;DR - VORTA accelerates video diffusion transformers by sparse attention and dynamic routing, achieving speedup with negligible quality loss.


## Quick Start

1. Download the checkpoints into the `./results` directory under the VORTA GitHub code repository.
```bash
git lfs install
git clone git@hf.co:anonymous728/VORTA
# mv VORTA/<model_name> results/, <model_name>: wan-14B, hunyuan; e.g.
mv VORTA/wan-14B results/
```
_Other alternative methods to download the models can be found [here](https://huggingface.co/docs/hub/models-downloading#using-git)._


2. Follow the `README.md` instructions to run the sampling with speedup. 🤗