Update Readme (#488)

README.md

@@ -20,7 +20,7 @@
 
 ## :fire: Latest News
 
-- **November 21, 2025:** 🚀 We support the HunyuanVideo1.5 video generation model since Day 0. With the same number of GPUs, LightX2V can deliver a speed improvement of over 2 times and supports deployment on GPUs with lower memory (such as the 24GB RTX 4090). It also supports CFG/Ulysses parallelism, efficient offloading, TeaCache/MagCache technologies, and more. We will soon update our models on our [HuggingFace page](https://huggingface.co/lightx2v), including quantization, step distillation, VAE distillation, and other related models.
+- **November 21, 2025:** 🚀 We support the HunyuanVideo1.5 video generation model since Day 0. With the same number of GPUs, LightX2V can achieve a speed improvement of over 2 times and supports deployment on GPUs with lower memory (such as the 24GB RTX 4090). It also supports CFG/Ulysses parallelism, efficient offloading, TeaCache/MagCache technologies, and more. We will soon update our models on our [HuggingFace page](https://huggingface.co/lightx2v), including quantization, step distillation, VAE distillation, and other related models. Refer to [this](https://github.com/ModelTC/LightX2V/tree/main/scripts/hunyuan_video_15) for usage tutorials.
 
 ## 💡 Quick Start
 

README_zh.md

@@ -20,7 +20,7 @@
 
 ## :fire: 最新动态
 
-- **2025年11月21日:** 🚀 我们Day0支持了HunyuanVideo1.5的视频生成模型，同样GPU数量，LightX2V可带来约2倍以上的速度提升，并支持更低显存GPU部署(如24G RTX4090)。支持CFG并行/Ulysses并行，高效Offload，TeaCache/MagCache等技术。同时支持沐曦，寒武纪等国产芯片部署。我们很快将在我们的[HuggingFace主页](https://huggingface.co/lightx2v)更新量化，步数蒸馏，VAE蒸馏等相关模型。
+- **2025年11月21日:** 🚀 我们Day0支持了HunyuanVideo1.5的视频生成模型，同样GPU数量，LightX2V可带来约2倍以上的速度提升，并支持更低显存GPU部署(如24G RTX4090)。支持CFG并行/Ulysses并行，高效Offload，TeaCache/MagCache等技术。同时支持沐曦，寒武纪等国产芯片部署。我们很快将在我们的[HuggingFace主页](https://huggingface.co/lightx2v)更新量化，步数蒸馏，VAE蒸馏等相关模型。使用教程参考[这里](https://github.com/ModelTC/LightX2V/tree/main/scripts/hunyuan_video_15)。
 
 
 ## 💡 快速开始

scripts/hunyuan_video_15/README.md

+# HunyuanVideo1.5
+
+## Quick Start
+
+1. Prepare docker environment:
+
+```bash
+docker pull lightx2v/lightx2v:25111101-cu128
+```
+
+2. Run the container:
+```bash
+docker run --gpus all -itd --ipc=host --name [container_name] -v [mount_settings] --entrypoint /bin/bash [image_id]
+```
+
+3. Prepare the models
+Please follow the instructions in [HunyuanVideo1.5 Github](https://github.com/Tencent-Hunyuan/HunyuanVideo-1.5/blob/main/checkpoints-download.md) to download and place the model files.
+
+4. Run the script
+```bash
+# enter the docker container
+
+git clone https://github.com/ModelTC/LightX2V.git
+cd LightX2V/scripts/hunyuan_video_15
+
+# set LightX2V path and model path in the script
+bash run_hy15_t2v_480p.sh
+```
+
+5. Check results
+You can find the generated video files in the `save_results` folder.
+
+6. Modify detailed configurations
+You can refer to the config file pointed to by `--config_json` in the script and modify its parameters as needed.