diff --git a/README.md b/README.md index c89119e..cb2cab3 100644 --- a/README.md +++ b/README.md @@ -40,7 +40,7 @@ HunyuanVideo-1.5 is a video generation model that delivers top-tier quality with - +
@@ -57,7 +57,7 @@ HunyuanVideo-1.5 is a video generation model that delivers top-tier quality with

## 🔥🔥🔥 News -* 🚀 Nov 24, 2025: We now support cache inference, achieving approximately 2x speedup! Pull the latest code to try it. +* 🚀 Nov 24, 2025: We now support cache inference, achieving approximately 2x speedup! Pull the latest code to try it. 🔥🔥🔥🆕 * 👋 Nov 20, 2025: We release the inference code and model weights of HunyuanVideo-1.5. @@ -76,6 +76,9 @@ If you develop/use HunyuanVideo-1.5 in your projects, welcome to let us know. - **LightX2V** - [LightX2V](https://github.com/ModelTC/LightX2V): A lightweight and efficient video generation framework that integrates HunyuanVideo-1.5, supporting multiple engineering acceleration techniques for fast inference. +- **Wan2GP v9.62** - [Wan2GP](https://github.com/deepbeepmeep/Wan2GP): WanGP is a very low VRAM app (as low 6 GB of VRAM for Hunyuan Video 1.5) supports Lora Accelerator for a 8 steps generation and offers tools to facilitate Video Generation. + + ## 📑 Open-source Plan - HunyuanVideo-1.5 (T2V/I2V) - [x] Inference Code and checkpoints @@ -400,12 +403,14 @@ We report the total inference time for 50 diffusion steps for HunyuanVideo 1.5 b ## 📚 Citation ```bibtex -@misc{hunyuanvideo2025, - title={HunyuanVideo 1.5 Technical Report}, +@misc{hunyuanvideo2025, + title={HunyuanVideo 1.5 Technical Report}, author={Tencent Hunyuan Foundation Model Team}, year={2025}, - publisher = {GitHub}, - howpublished = {\url{https://github.com/Tencent-Hunyuan/HunyuanVideo-1.5}}, + eprint={2511.18870}, + archivePrefix={arXiv}, + primaryClass={cs.CV}, + url={https://arxiv.org/abs/2511.18870}, } ``` diff --git a/README_CN.md b/README_CN.md index 0527f46..88132c6 100644 --- a/README_CN.md +++ b/README_CN.md @@ -24,7 +24,7 @@ HunyuanVideo-1.5作为一款轻量级视频生成模型,仅需83亿参数即 - +
@@ -40,7 +40,7 @@ HunyuanVideo-1.5作为一款轻量级视频生成模型,仅需83亿参数即

## 🔥🔥🔥 最新动态 -* 🚀 Nov 24, 2025: 我们现已支持 cache 推理,可实现约两倍加速!请 pull 最新代码体验。 +* 🚀 Nov 24, 2025: 我们现已支持 cache 推理,可实现约两倍加速!请 pull 最新代码体验。 🔥🔥🔥🆕 * 👋 Nov 20, 2025: 我们开源了 HunyuanVideo-1.5的代码和推理权重 ## 🎥 演示视频 @@ -58,6 +58,9 @@ HunyuanVideo-1.5作为一款轻量级视频生成模型,仅需83亿参数即 - **LightX2V** - [LightX2V](https://github.com/ModelTC/LightX2V): 一个轻量级高效的视频生成框架,集成了 HunyuanVideo-1.5,支持多种工程加速技术以实现快速推理。 +- **Wan2GP v9.62** - [Wan2GP](https://github.com/deepbeepmeep/Wan2GP): Wan2GP 是一款对显存要求非常低的应用(在 Hunyuan Video 1.5 下最低仅需 6GB 显存),支持 Lora 加速器实现 8 步生成,并且提供多种视频生成辅助工具。 + + ## 📑 开源计划 - HunyuanVideo-1.5 (文生视频/图生视频) - [x] 推理代码和模型权重 @@ -381,12 +384,14 @@ GSB(Good/Same/Bad)评估法被广泛用于基于整体视频感知质量来 ## 📚 引用 ```bibtex -@misc{hunyuanvideo2025, - title={HunyuanVideo 1.5 Technical Report}, +@misc{hunyuanvideo2025, + title={HunyuanVideo 1.5 Technical Report}, author={Tencent Hunyuan Foundation Model Team}, year={2025}, - publisher = {GitHub}, - howpublished = {\url{https://github.com/Tencent-Hunyuan/HunyuanVideo-1.5}}, + eprint={2511.18870}, + archivePrefix={arXiv}, + primaryClass={cs.CV}, + url={https://arxiv.org/abs/2511.18870}, } ```