Improve pipeline tag and add library name; incorporate relevant information from Github README

README.md

@@ -1,13 +1,101 @@
 ---
-license: mit
-language:
-- en
 base_model:
 - Qwen/Qwen2.5-VL-3B-Instruct
-pipeline_tag: visual-question-answering
+language:
+- en
+license: mit
+pipeline_tag: image-text-to-text
+library_name: transformers
 ---
 
-
 This repository contains the model presented in [UI-R1: Enhancing Action Prediction of GUI Agents by Reinforcement Learning](https://huggingface.co/papers/2503.21620).
 
-Project page: https://github.com/lll6gg/UI-R1
+Project page: https://github.com/lll6gg/UI-R1
+
+## Setup
+
+```shell
+conda create -n ui-r1 python=3.10
+conda activate ui-r1
+bash setup.sh
+```
+
+## Data
+
+Our training mobile data is a subset from AndroidControl and ScreenSpot.
+
+You can also prepare your training or inference data like:
+
+```
+images/:
+	image1.png
+	image2.png
+```
+
+```
+test.json:
+[
+	{
+	"img_filename": "image1.png",
+        "bbox": [
+            825,
+            72,
+            1673,
+            149
+        ],
+        "instruction": "search bar"
+     },
+     {
+	"img_filename": "image2.png",
+        "bbox": [
+            123,
+            732,
+            334,
+            812
+        ],
+        "instruction": "check weather"
+     }
+]
+```
+
+where bbox : [x1,y1,x2,y2] is the coordinate of the left top and the right bottom of the ground truth bbox
+
+## Inference
+
+We provide an example here
+
+```shell
+cd evaluation/
+bash test.sh
+```
+
+Please fill the MODEL_PATH, IMG_PATH, TEST_JSON with your real checkpoint path and data path.
+## Training
+
+```shell
+cd src/script/
+bash train.sh
+```
+
+## 🗞️ News
+- **`2025-04-02`**: We release the [datasets](https://huggingface.co/datasets/LZXzju/UI-R1-3B-Train) of the UI-R1-3B model.
+- **`2025-03-30`**: We release the [checkpoints](https://huggingface.co/LZXzju/Qwen2.5-VL-3B-UI-R1) of the UI-R1-3B model.
+- **`2025-03-30`**: We release the UI-R1 repository.
+- **`2025-03-27`**: We release our [paper](https://arxiv.org/abs/2503.21620).
+
+## ⭐️ Citation
+
+If you find this project useful, welcome to cite us.
+
+```bit
+@article{lu2025ui,
+  title={UI-R1: Enhancing Action Prediction of GUI Agents by Reinforcement Learning},
+  author={Lu, Zhengxi and Chai, Yuxiang and Guo, Yaxuan and Yin, Xi and Liu, Liang and Wang, Hao and Xiong, Guanjing and Li, Hongsheng},
+  journal={arXiv preprint arXiv:2503.21620},
+  year={2025}
+}
+```
+
+## 🤝 Acknowledgements
+
+We sincerely thank projects [R1-V](https://github.com/Deep-Agent/R1-V), [Open-R1](https://github.com/huggingface/open-r1), and [Open-r1-multimodal](https://github.com/EvolvingLMMs-Lab/open-r1-multimodal), [VLM-R1](https://github.com/om-ai-lab/VLM-R1) for providing their open-source resources.