Update README.md

README.md

-### 复现指南🔥🔥🔥
+```markdown
+# hunyuan-dit
 
-```shell
-# 1. 环境准备
+> A high-performance implementation of the HunyuanDiT model for text-to-image generation.  
+> This project provides an environment setup, dependency installation, and usage instructions to reproduce and run the model efficiently using Docker and optimized hardware libraries.
+
+---
+
+## 🔥 复现指南 (Reproduction Guide)
+
+### 1. 环境准备 (Prepare Environment)
+
+Pull the required Docker image:
+
+```bash
 docker pull image.sourcefind.cn:5000/dcu/admin/base/vllm:0.9.2-ubuntu22.04-dtk25.04.1-rc5-rocblas101839-0811-das1.6-py3.10-20250908-rc1
+```
+
+### 2. 创建容器 (Create Container)
 
-# 2. 创建容器
+Run a Docker container with proper configurations:
+
+```bash
 docker run -it \
---network=host \
---hostname=localhost \
---name=HUNYUAN \
--v /opt/hyhal:/opt/hyhal:ro \
--v $PWD:/workspace \
---ipc=host \
---device=/dev/kfd \
---device=/dev/mkfd \
---device=/dev/dri \
---shm-size=512G \
---privileged \
---group-add video \
---cap-add=SYS_PTRACE \
---security-opt seccomp=unconfined \
-image.sourcefind.cn:5000/dcu/admin/base/vllm:0.9.2-ubuntu22.04-dtk25.04.1-rc5-rocblas101839-0811-das1.6-py3.10-20250908-rc1 \
-/bin/bash  
-
-# 3. 拉取代码
+  --network=host \
+  --hostname=localhost \
+  --name=HUNYUAN \
+  -v /opt/hyhal:/opt/hyhal:ro \
+  -v $PWD:/workspace \
+  --ipc=host \
+  --device=/dev/kfd \
+  --device=/dev/mkfd \
+  --device=/dev/dri \
+  --shm-size=512G \
+  --privileged \
+  --group-add video \
+  --cap-add=SYS_PTRACE \
+  --security-opt seccomp=unconfined \
+  image.sourcefind.cn:5000/dcu/admin/base/vllm:0.9.2-ubuntu22.04-dtk25.04.1-rc5-rocblas101839-0811-das1.6-py3.10-20250908-rc1 \
+  /bin/bash
+```
+
+### 3. 拉取代码 (Clone Repository)
+
+```bash
 git clone http://developer.sourcefind.cn/codes/bw_bestperf/hunyuan-dit.git
+cd hunyuan-dit
+```
+
+### 4. 获取 & 安装依赖 (Download & Install Dependencies)
 
-# 4. 获取&安装依赖
-Apex:
-curl -f -C - -o apex-1.5.0+das.opt1.dtk25041-cp310-cp310-linux_x86_64.whl https://ksefile.hpccube.com:65241/efile/s/d/amVycnJycnk=/e759f4e7fbb64b10  
-Lightop
-curl -f -C - -o lightop-0.5.0+das.dtk25041.unknown-cp310-cp310-linux_x86_64.whl https://ksefile.hpccube.com:65241/efile/s/d/amVycnJycnk=/3ca9654a8fc1b0b5  
-Deepspeed
+Download required custom wheels:
+
+```bash
+# Apex
+curl -f -C - -o apex-1.5.0+das.opt1.dtk25041-cp310-cp310-linux_x86_64.whl https://ksefile.hpccube.com:65241/efile/s/d/amVycnJycnk=/e759f4e7fbb64b10
+
+# Lightop
+curl -f -C - -o lightop-0.5.0+das.dtk25041.unknown-cp310-cp310-linux_x86_64.whl https://ksefile.hpccube.com:65241/efile/s/d/amVycnJycnk=/3ca9654a8fc1b0b5
+
+# Deepspeed
 wget https://download.sourcefind.cn:65024/directlink/4/deepspeed/DAS1.6/deepspeed-0.14.2+das.opt1.dtk25041-cp310-cp310-manylinux_2_28_x86_64.whl
+```
+
+Install the wheels and requirements:
 
-pip install apex-1.5.0+das.opt1.dtk25041-cp310-cp310-linux_x86_64.whl 
-pip install lightop-0.5.0+das.dtk25041.unknown-cp310-cp310-linux_x86_64.whl 
+```bash
+pip install apex-1.5.0+das.opt1.dtk25041-cp310-cp310-linux_x86_64.whl
+pip install lightop-0.5.0+das.dtk25041.unknown-cp310-cp310-linux_x86_64.whl
 pip install deepspeed-0.14.2+das.opt1.dtk25041-cp310-cp310-manylinux_2_28_x86_64.whl
-pip install -r requirements.txt   -i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
+pip install -r requirements.txt -i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
+```
+
+### 5. 下载优化包 (Download Optimization Packages)
+
+```bash
+curl -f -C - -o hipblaslt-install0925.tar.gz https://ksefile.hpccube.com:65241/efile/s/d/amVycnJycnk=/5857030947151012
+curl -f -C - -o package_0915_ubuntu.tar.gz https://ksefile.hpccube.com:65241/efile/s/d/amVycnJycnk=/0c80d0e60b9af80d
+```
+
+Extract and install them accordingly as per your environment needs.
+
+### 6. 下载模型 (Download Model)
+
+Refer to the model page on ModelScope:  
+https://modelscope.cn/models/dengcao/HunyuanDiT-v1.2
 
-# 5. 下载优化包
-hipblaslt
-curl -f -C - -o hipblaslt-install0925.tar.gz https://ksefile.hpccube.com:65241/efile/s/d/amVycnJycnk=/5857030947151012  
-miopen
-curl -f -C - -o package_0915_ubuntu.tar.gz https://ksefile.hpccube.com:65241/efile/s/d/amVycnJycnk=/0c80d0e60b9af80d 
+Commands to download and prepare:
 
-# 6. 下载模型
-模型详见：https://modelscope.cn/models/dengcao/HunyuanDiT-v1.2 
+```bash
+pip install modelscope
+
+modelscope download --model dengcao/HunyuanDiT-v1.2 --local_dir ./HunyuanDiT-v1.2
 
-pip install modelscope 
-modelscope download --model dengcao/HunyuanDiT-v1.2  --local_dir ./HunyuanDiT-v1.2
-还需要下载vae,tokenizer和tex_encoder
 cd HunyuanDiT-v1.2
+
 wget https://dit.hunyuan.tencent.com/download/HunyuanDiT/tokenizer.zip
 wget https://dit.hunyuan.tencent.com/download/HunyuanDiT/sdxl-vae-fp16-fix.zip
 wget https://dit.hunyuan.tencent.com/download/HunyuanDiT/clip_text_encoder.zip
+```
 
-下载完模型结构如下
-
+Model directory structure after download:
 
-```
 <p align="center">
-  <img src="19115934112c36d5d67394265d1498e2.png"  height=300>
+  <img src="19115934112c36d5d67394265d1498e2.png" height="300" alt="Model Directory Structure">
 </p>
 
-## 测试指令
+---
 
-```
+## 测试指令 (Test Command)
+
+Set library paths and run inference:
+
+```bash
 export LD_LIBRARY_PATH=/workspace/OEM_ADVTG_TEST/hunyuan/hipblaslt-install/lib/:$LD_LIBRARY_PATH
 export LD_LIBRARY_PATH=/workspace/OEM_ADVTG_TEST/hunyuan/package/miopen/lib/:$LD_LIBRARY_PATH
-python sample_t2i_dcu.py --model-root /workspace/OEM_ADVTG_TEST/hunyuan/HunyuanDiT-v1.2/ --batch-size 4 --infer-mode fa --prompt "青花瓷风格，一只可爱的哈士奇" --no-enhance  --load-key module --image-size 1024 1024 --infer-steps 20 
 
+python sample_t2i_dcu.py \
+  --model-root /workspace/OEM_ADVTG_TEST/hunyuan/HunyuanDiT-v1.2/ \
+  --batch-size 4 \
+  --infer-mode fa \
+  --prompt "青花瓷风格，一只可爱的哈士奇" \
+  --no-enhance \
+  --load-key module \
+  --image-size 1024 1024 \
+  --infer-steps 20
+```
+
+---
+
+## 配置选项 (Configuration Options)
+
+| Option       | Description                                 | Default / Example                  |
+|--------------|---------------------------------------------|----------------------------------|
+| `--model-root` | Path to the downloaded model directory     | `/workspace/OEM_ADVTG_TEST/hunyuan/HunyuanDiT-v1.2/` |
+| `--batch-size` | Batch size for inference                     | 4                                |
+| `--infer-mode` | Inference mode (e.g., "fa")                  | "fa"                            |
+| `--prompt`     | Text prompt for image generation             | `"青花瓷风格，一只可爱的哈士奇"`   |
+| `--no-enhance` | Disable image enhancement                     | Flag                            |
+| `--load-key`   | Key for loading model weights                 | `module`                        |
+| `--image-size` | Output image size `[width] [height]`          | `1024 1024`                     |
+| `--infer-steps`| Number of inference steps                      | 20                             |
+
+---
+
+## 贡献指南 (Contributing)
+
+We welcome contributions! Please follow the steps below to contribute:
+
+1. Fork the repository.
+2. Create a feature branch: `git checkout -b feature-name`.
+3. Make your changes and commit with clear messages.
+4. Open a Pull Request describing your changes.
+5. Ensure code passes tests and adheres to project style.
+
+Please report issues and suggest improvements via the issue tracker.
+
+---
+
+## 许可证 (License)
+
+This project is licensed under the **[MIT License](./LICENSE)**.  
+Feel free to use, modify, and distribute under the terms of this license.
+
+---
+
+## 联系方式 (Contact)
+
+For any questions or support, please contact the maintainers via the repository issue page.
+
+---
+
+Thank you for using **hunyuan-dit**! Enjoy exploring the power of text-to-image models.
 ```