⚡️ LightX2V:
Light Video Generation Inference Framework

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-------------------------------------------------------------------------------- **LightX2V** is a lightweight video generation inference framework designed to provide an inference tool that leverages multiple advanced video generation inference techniques. As a unified inference platform, this framework supports various generation tasks such as text-to-video (T2V) and image-to-video (I2V) across different models. **X2V means transforming different input modalities (such as text or images) to video output.** ## 💡 How to Start Please refer to our documentation: **[English Docs](https://lightx2v-en.readthedocs.io/en/latest/) | [中文文档](https://lightx2v-zhcn.readthedocs.io/zh-cn/latest/)**. ## 🤖 Supported Model List - ✅ [HunyuanVideo-T2V](https://huggingface.co/tencent/HunyuanVideo) - ✅ [HunyuanVideo-I2V](https://huggingface.co/tencent/HunyuanVideo-I2V) - ✅ [Wan2.1-T2V](https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B) - ✅ [Wan2.1-I2V](https://huggingface.co/Wan-AI/Wan2.1-I2V-14B-480P) - ✅ [Wan2.1-T2V-StepDistill-CfgDistill](https://huggingface.co/lightx2v/Wan2.1-T2V-14B-StepDistill-CfgDistill) - ✅ [Wan2.1-T2V-CausVid](https://huggingface.co/lightx2v/Wan2.1-T2V-14B-CausVid) - ✅ [SkyReels-V2-DF](https://huggingface.co/Skywork/SkyReels-V2-DF-14B-540P) - ✅ [CogVideoX1.5-5B-T2V](https://huggingface.co/THUDM/CogVideoX1.5-5B) ## 🧾 Contributing Guidelines We have prepared a pre-commit hook to enforce consistent code formatting across the project. > [!TIP] > - Install the required dependencies: > > ```shell > pip install ruff pre-commit >``` > > - Then, run the following command before commit: > > ```shell > pre-commit run --all-files >``` Thank you for your contributions! ## 🤝 Acknowledgments We built the code for this repository by referencing the code repositories involved in all the models mentioned above. ## 🌟 Star History [![Star History Chart](https://api.star-history.com/svg?repos=ModelTC/lightx2v&type=Timeline)](https://star-history.com/#ModelTC/llmc&Timeline) ## ✏️ Citation If you find our framework useful to your research, please kindly cite our work: ``` @misc{lightx2v, author = {lightx2v contributors}, title = {LightX2V: Light Video Generation Inference Framework}, year = {2024}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url{https://github.com/ModelTC/lightx2v}}, } ```