Update README.md

README.md

@@ -5,26 +5,38 @@ language:
 ---
 # CogAgent
 
-## Introduction
-
 **CogAgent** is an open-source visual language model improved based on **CogVLM**. 
 
 📖 Paper: https://arxiv.org/abs/2312.08914
 
-**CogAgent-18B** has 11 billion visual parameters and 7 billion language parameters and achieves state-of-the-art generalist performance on 9 classic cross-modal benchmarks, including:
-  + VQAv2 
-  + OK-VQ
-  + TextVQA 
-  + ST-VQA
-  + ChartQA 
-  + infoVQA 
-  + DocVQA 
-  + MM-Vet 
-  + POPE
+🚀 GitHub: For more information such as demo, fine-tuning, and query prompts, please refer to [Our GitHub](https://github.com/THUDM/CogVLM/)
+
+## Reminder
+
+**This is the ``cogagent-vqa`` version of CogAgent checkpoint.**
+
+We have open-sourced two versions of CogAgent checkpoints, and you can choose one based on your needs. 
+
+1. ``cogagent-chat``: This model has strong capabilities in **GUI Agent, visual multi-turn dialogue, visual grounding,** etc.
+
+   If you need GUI Agent and Visual Grounding functions, or need to conduct multi-turn dialogues with a given image, we recommend using this version of the model.
 
-**CogAgent-18B** significantly surpasses existing models on GUI operation datasets such as AITW and Mind2Web.
+3. ``cogagent-vqa``: This model has *stronger* capabilities in **single-turn visual dialogue**.
+  
+   If you need to **work on VQA leaderboards** (such as MMVET, VQAv2), we recommend using this model.
+   
 
-In addition to all the features already present in **CogVLM** (visual multi-round dialogue, visual grounding), **CogAgent**:
+## Introduction
+
+CogAgent-18B has 11 billion visual and 7 billion language parameters.
+
+CogAgent demonstrates **strong performance** in image understanding and GUI agent:
+
+1. CogAgent-18B **achieves state-of-the-art generalist performance on 9 cross-modal benchmarks**, including: VQAv2, MM-Vet, POPE, ST-VQA, OK-VQA, TextVQA, ChartQA, InfoVQA, DocVQA. 
+
+2. CogAgent-18B significantly **surpasses existing models on GUI operation datasets**, including AITW and Mind2Web.
+
+In addition to all the **features** already present in **CogVLM** (visual multi-round dialogue, visual grounding), **CogAgent**:
 
 1. Supports higher resolution visual input and dialogue question-answering. It supports ultra-high-resolution image inputs of **1120x1120**.
 
@@ -124,7 +136,7 @@ Then run:
 ```bash
 python cli_demo_hf.py --bf16
 ```
-for more information such as Web Demo and Finetune, please refer to [Our GitHub](https://github.com/THUDM/CogVLM/)
+
 
 ## License