Update README.md

README.md

@@ -5,16 +5,27 @@ base_model: OpenGVLab/InternVL2-4B
 pipeline_tag: image-text-to-text
 ---
 
-This repository contains the model of the paper [OS-ATLAS: A Foundation Action Model for Generalist GUI Agents](https://huggingface.co/papers/2410.23218).
+# OS-Atlas: A Foundation Action Model For Generalist GUI Agents
 
 <div align="center">
 
-[\[🏠Homepage\]](https://osatlas.github.io) [\[💻Code\]](https://github.com/OS-Copilot/OS-Atlas) [\[🚀Quick Start\]](#quick-start) [\[📝Paper\]](https://arxiv.org/abs/2410.23218) [\[🤗Models\]](https://huggingface.co/collections/OS-Copilot/os-atlas-67246e44003a1dfcc5d0d045) [\[🤗ScreenSpot-v2\]](https://huggingface.co/datasets/OS-Copilot/ScreenSpot-v2) 
+[\[🏠Homepage\]](https://osatlas.github.io) [\[💻Code\]](https://github.com/OS-Copilot/OS-Atlas) [\[🚀Quick Start\]](#quick-start) [\[📝Paper\]](https://arxiv.org/abs/2410.23218) [\[🤗Models\]](https://huggingface.co/collections/OS-Copilot/os-atlas-67246e44003a1dfcc5d0d045)[\[🤗Data\]](https://huggingface.co/datasets/OS-Copilot/OS-Atlas-data) [\[🤗ScreenSpot-v2\]](https://huggingface.co/datasets/OS-Copilot/ScreenSpot-v2) 
 
 </div>
 
+## Overview
 ![os-atlas](https://github.com/user-attachments/assets/cf2ee020-5e15-4087-9a7e-75cc43662494)
 
+OS-Atlas provides a series of models specifically designed for GUI agents.
+
+For GUI grounding tasks, you can use:
+- [OS-Atlas-Base-7B](https://huggingface.co/OS-Copilot/OS-Atlas-Base-7B)
+- [OS-Atlas-Base-4B](https://huggingface.co/OS-Copilot/OS-Atlas-Base-4B)
+
+For generating single-step actions in GUI agent tasks, you can use:
+- [OS-Atlas-Pro-7B](https://huggingface.co/OS-Copilot/OS-Atlas-Pro-7B)
+- [OS-Atlas-Pro-4B](https://huggingface.co/OS-Copilot/OS-Atlas-Pro-4B)
+
 ## Quick Start
 OS-Atlas-Base-4B is a GUI grounding model finetuned from [InternVL2-4B](https://huggingface.co/OpenGVLab/InternVL2-4B).
 
@@ -27,6 +38,8 @@ pip install transformers
 ```
 For additional dependencies, please refer to the [InternVL2 documentation](https://internvl.readthedocs.io/en/latest/get_started/installation.html)
 
+Then download the [example image](https://github.com/OS-Copilot/OS-Atlas/blob/main/examples/images/web_dfacd48d-d2c2-492f-b94c-41e6a34ea99f.png) and save it to the current directory.
+
 Inference code example:
 ```python
 import numpy as np
@@ -119,7 +132,7 @@ model = AutoModel.from_pretrained(
 tokenizer = AutoTokenizer.from_pretrained(path, trust_remote_code=True, use_fast=False)
 
 # set the max number of tiles in `max_num`
-pixel_values = load_image('https://github.com/OS-Copilot/OS-Atlas/blob/main/exmaples/images/web_dfacd48d-d2c2-492f-b94c-41e6a34ea99f.png', max_num=6).to(torch.bfloat16).cuda()
+pixel_values = load_image('./web_dfacd48d-d2c2-492f-b94c-41e6a34ea99f.png', max_num=6).to(torch.bfloat16).cuda()
 generation_config = dict(max_new_tokens=1024, do_sample=True)
 
 question = "In the screenshot of this web page, please give me the coordinates of the element I want to click on according to my instructions(with point).\n\"'Champions League' link\""