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README.md
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## Overview
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**AgentCPM-GUI** is an open-source on-device LLM agent model jointly developed by [THUNLP](https://nlp.csai.tsinghua.edu.cn) and [ModelBest](https://modelbest.cn/en). Built on [MiniCPM-V](https://github.com/OpenBMB/MiniCPM-V) with 8 billion parameters, it accepts smartphone screenshots as input and autonomously executes user-specified tasks.
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Key features include:
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```bash
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git clone https://github.com/OpenBMB/AgentCPM-GUI
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cd
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conda create -n gui_agent python=3.11
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conda activate gui_agent
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pip install -r requirements.txt
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## Fine-tuning
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Source code for SFT and RFT training is provided — see [
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## Performance Evaluation
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> \*Different train/test splits
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All evaluation data and code are open-sourced — see [here](eval) for details.
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## Evaluation Data
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## Overview
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**AgentCPM-GUI** is an open-source on-device LLM agent model jointly developed by [THUNLP](https://nlp.csai.tsinghua.edu.cn), Renmin University of China and [ModelBest](https://modelbest.cn/en). Built on [MiniCPM-V](https://github.com/OpenBMB/MiniCPM-V) with 8 billion parameters, it accepts smartphone screenshots as input and autonomously executes user-specified tasks.
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Key features include:
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```bash
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git clone https://github.com/OpenBMB/AgentCPM-GUI
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cd AgentCPM-GUI
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conda create -n gui_agent python=3.11
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conda activate gui_agent
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pip install -r requirements.txt
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## Fine-tuning
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Source code for SFT and RFT training is provided — see [GitHub](https://github.com/OpenBMB/AgentCPM-GUI).
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## Performance Evaluation
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> \*Different train/test splits
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TM and EM stand for the **Type Match** and **Exact Match**, respectively. All evaluation data and code are open-sourced — see [here](eval) for details.
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All evaluation data and code are open-sourced — see [here](https://github.com/OpenBMB/AgentCPM-GUI/tree/main/eval) for details.
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## Evaluation Data
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