The "KwaiAgents" system, jointly open sourced by Kuaishou and Harbin Institute of Technology, relies on the Meta-Agent Tuning (MAT) method to make the 7B/13B model surpass GPT-3.5 in performance, attracting industry attention. This system is based on a large model, combined with a memory mechanism and a tool library, to build an automated system. Its core highlight is that the MAT method effectively avoids the problem of model overfitting and significantly improves the generalization ability and practicality of the model. This move not only provides valuable resources for researchers in the field of artificial intelligence, but also injects new vitality into the further development of large model technology.
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Kuaishou and Harbin Institute of Technology jointly open sourced the "KwaiAgents" system. Through the Meta-Agent Tuning method, the 7B/13B model surpassed GPT-3.5 in all aspects. The system takes a large model as the core and forms an automated system through a memory mechanism and tool library. The MAT method avoids the over-fitting problem and improves the general ability of the model. Open source projects inject new vitality and provide researchers with rich resources.
The open source of the KwaiAgents system provides new directions and wider application possibilities for large model research, and also indicates that large model technology will develop in a more practical and general direction in the future. We look forward to more research results based on this system in the future.