cogagent-9b-20241220

CogAgent-9B-20241220 is a GUI agent model based on visual language models.

CommonProductProgrammingvisual language modelGUI agent

The CogAgent-9B-20241220 model is developed on the GLM-4V-9B bilingual open-source visual language model. Through data collection and optimization, multi-stage training, and strategy improvements, it has made significant advancements in GUI perception, inference prediction accuracy, action space completeness, and task generalization capabilities. This model supports bilingual interaction (Chinese and English) and can handle screenshots and language input. The current version has been implemented in ZhipuAI's GLM-PC product, aimed at helping researchers and developers progress in the study and application of visual language model-based GUI agents.

• GUI Perception: The model can understand and handle tasks related to graphical user interfaces (GUIs).
• Inference Prediction: The model can provide accurate inference predictions to assist in executing GUI tasks.
• Action Space Completeness: The model can understand and execute a complete action space
covering various GUI operations.
• Task Generalization: The model has strong task generalization capabilities
capable of handling a wide range of GUI tasks.
• Bilingual Interaction: The model supports interactions in both Chinese and English
catering to users of different languages.
• Multi-Stage Training: The model has been optimized through multi-stage training
enhancing performance and accuracy.

\Target audience includes researchers and developers
particularly professionals focusing on artificial intelligence
natural language processing
and computer vision. The CogAgent-9B-20241220 model assists them in building and optimizing visual language model-based GUI agents
advancing related technology research and application.\

Example 1: Researchers use the CogAgent-9B-20241220 model to develop a GUI agent capable of automating software testing.
Example 2: Developers leverage this model to create an automation tool that performs web operations based on user instructions.
Example 3: Companies utilize the CogAgent-9B-20241220 model to enhance the user experience of their software products by automating common tasks and reducing operational complexity for users.

1. Visit the GitHub page for specific examples on how to run the model.
2. Format user input according to the model's input/output guidelines
and explain the formatted output.
3. Be aware of the prompting connection process; refer to specific code examples on GitHub for user input prompting connections.
4. Ensure compliance with the model's licensing agreement when using it.

Visit

cogagent-9b-20241220 Visit Over Time

Monthly Visits

20899836

Bounce Rate

46.04%

Page per Visit

5.2

Visit Duration

00:04:57

cogagent-9b-20241220 Visit Trend

cogagent-9b-20241220 Visit Geography

cogagent-9b-20241220 Traffic Sources

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cogagent-9b-20241220

cogagent-9b-20241220 Visit Over Time

cogagent-9b-20241220 Visit Trend

cogagent-9b-20241220 Visit Geography

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