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# LightX2V: Light Video Generation Inference Framework
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<div align="center" id="lightx2v">
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<img alt="logo" src="assets/img_lightx2v.png" width=75%></img>
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[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
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[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/ModelTC/lightx2v)
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[![Doc](https://img.shields.io/badge/docs-English-99cc2)](https://lightx2v-en.readthedocs.io/en/latest)
[![Doc](https://img.shields.io/badge/文档-中文-99cc2)](https://lightx2v-zhcn.readthedocs.io/zh-cn/latest)
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[![Docker](https://badgen.net/badge/icon/docker?icon=docker&label)](https://hub.docker.com/r/lightx2v/lightx2v/tags)
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</div>

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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.**
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## 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/)


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## 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)

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[Wan2.1-T2V-StepDistill-CfgDistill](https://huggingface.co/lightx2v/Wan2.1-T2V-14B-StepDistill-CfgDistill)

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[Wan2.1-T2V-CausVid](https://huggingface.co/lightx2v/Wan2.1-T2V-14B-CausVid)

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[SkyReels-V2-DF](https://huggingface.co/Skywork/SkyReels-V2-DF-14B-540P)
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[CogVideoX1.5-5B-T2V](https://huggingface.co/THUDM/CogVideoX1.5-5B)
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## Contributing Guidelines
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We have prepared a `pre-commit` hook to enforce consistent code formatting across the project.
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1. Install the required dependencies:

```shell
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pip install ruff pre-commit
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```

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2. Then, run the following command before commit:
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```shell
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pre-commit run --all-files
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```

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Thank you for your contributions!
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## Acknowledgments

We built the code for this repository by referencing the code repositories involved in all the models mentioned above.