update README.md file

README.md

@@ -1,11 +1,17 @@
 **Read this in other languages: [English](README.md), [中文](README_zh.md).**
+
 # OpenVLA Lightweight Version
 
-OpenVLA的轻量化版本，基于llava-next框架
-特点：
-1.主体模型仅0.5B，使用qwen2-0.5B
-2.不使用RLDS格式数据集，使用mllm格式进行微调
-3.不占用LLM模型固有tokens,使用新增的271个tokens表示动作
+Lightweight version of OpenVLA, based on the llava-next framework
+
+Features:
+
+1.The main model is only 0.5B, using qwen2-0.5B.
+
+2.Does not use RLDS format datasets, instead fine-tuned using mllm format.
+
+3.Does not occupy inherent tokens of the LLM model, instead using an additional 271 tokens to represent actions.
+# How to use
 
 ## Installation
 
@@ -29,9 +35,24 @@ conda activate vla-qwen
 pip install --upgrade pip
 pip install -e ".[train]"
 ```
+### 4. Download the weights from huggingface
+```bash
+cd openVLA-Qwen/models
+git clone git clone https://huggingface.co/lmms-lab/llava-onevision-qwen2-0.5b-ov
+```
+### 5. Change the file path in scripts/train/finetune_ov_vla.sh
+```bash
+PREV_STAGE_CHECKPOINT="models/llava-onevision-qwen2-0.5b-ov" 
+--data_path scripts/train/vla.yaml
+--image_folder /images \
+```
+### 6. Change the data paht in scripts/train/vla.yaml
+```bash
+json_path: /root/data/vla_llava.json
+```
 ## Acknowledgements
 
-I would like to express my gratitude to the following repositories:
+This project makes use of the following open-source projects, and I would like to express my gratitude to their creators:
 
 - [OpenVLA](https://github.com/openvla/openvla) - For providing the core structure and functionality that inspired OpenVLA-Qwen.
 - [LLaVA_OpenVLA](https://github.com/Darren-greenhand/LLaVA-Next) - For his contribution to data preprocessing techniques.