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--- |
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license: cc-by-nc-4.0 |
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task_categories: |
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- text-to-video |
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size_categories: |
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- n>1T |
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--- |
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# Wan-synthesized datasets for Video Diffusion Distillation |
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[**TurboDiffusion Paper**](https://huggingface.co/papers/2512.16093) | [**rCM Paper**](https://arxiv.org/abs/2510.08431) | [**Project Page**](https://github.com/thu-ml/TurboDiffusion) | [**Code**](https://github.com/thu-ml/TurboDiffusion) |
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This repository holds Wan-synthesized datasets used for training [TurboDiffusion](https://github.com/thu-ml/TurboDiffusion) and [rCM (Score-Regularized Continuous-Time Consistency Model)](https://research.nvidia.com/labs/dir/rcm). |
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These datasets consist of large-scale synthetic videos generated by Wan2.1 models (including the 1.3B and 14B variants) at various resolutions (480p, 720p). They are primarily used for diffusion distillation tasks like rCM training and Sparse-Linear Attention (SLA) alignment. |
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<video src="https://github.com/user-attachments/assets/7186a410-bdcc-45d0-a320-d8a66c913914" controls></video> |
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## Dataset Structure |
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The data is provided in `webdataset` format, consisting of sharded `.tar` files. A typical directory structure looks like: |
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``` |
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Wan2.1_14B_480p_16:9_Euler-step100_shift-3.0_cfg-5.0_seed-0_250K/ |
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shard00000.tar |
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shard00001.tar |
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... |
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``` |
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## Usage |
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### Downloading the data |
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You can download the dataset shards using `git lfs`: |
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```bash |
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# Make sure git lfs is installed |
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git clone https://huggingface.co/datasets/worstcoder/Wan_datasets |
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``` |
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### Loading in Training |
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In the TurboDiffusion/rCM training pipeline, the dataset can be accessed using a pattern-based loader: |
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```bash |
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# Example path pattern for training configuration |
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dataloader_train.tar_path_pattern="assets/datasets/Wan2.1_14B_480p_.../shard*.tar" |
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``` |
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## Citation |
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If you use this dataset, please cite the following works: |
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```bibtex |
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@article{zhang2025turbodiffusion, |
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title={TurboDiffusion: Accelerating Video Diffusion Models by 100-200 Times}, |
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author={Zhang, Jintao and Zheng, Kaiwen and Jiang, Kai and Wang, Haoxu and Stoica, Ion and Gonzalez, Joseph E and Chen, Jianfei and Zhu, Jun}, |
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journal={arXiv preprint arXiv:2512.16093}, |
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year={2025} |
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} |
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@article{zheng2025rcm, |
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title={Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency}, |
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author={Zheng, Kaiwen and Wang, Yuji and Ma, Qianli and Chen, Huayu and Zhang, Jintao and Balaji, Yogesh and Chen, Jianfei and Liu, Ming-Yu and Zhu, Jun and Zhang, Qinsheng}, |
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journal={arXiv preprint arXiv:2510.08431}, |
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year={2025} |
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} |
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``` |
