#AgentLM

AgentTuning improves the general agent abilities of LLMs by using interaction trajectories for instruction tuning. The open-source AgentInstruct dataset and AgentLM models provide carefully curated interactions for enhancing AI performance in various real-world scenarios. This methodology shows strong generalization on new tasks while maintaining language capabilities. Models available on Huggingface are evaluated through tasks ranging from AgentBench to scientific and gaming applications, providing detailed insights into the capabilities and effectiveness of these enhanced LLM agents. Discover the innovative approaches employed by this project and its impact on generalized agent abilities.