[Paper] [Homepage] [Dataset] [Github] Welcome to the xLAM 2 Model Family! Large Action Models (LAMs) are advanced language models designed to enhance decision making by translating user intentions into executable actions. As the brains of AI agents , LAMs autonomously plan and execute tasks to achieve specific goals, making them invaluable for automating workflows across diverse domains. This model release is for research purposes only. The new xLAM 2 series, built on our most advanced data synthesis, processing, and training pipelines, marks a significant leap in multi turn conversation and tool usage . Trained using our novel APIGen MT framework, which generates high quality training data through simulated agent human interactions. Our models achieve state of the art performance on BFCL and τ bench benchmarks, outperforming frontier models like GPT 4o and Claude 3.5. Notably, even our smaller models demonstrate superior capabilities in multi turn scenarios while maintaining exceptional consistency across trials. We've also refined the chat template and vLLM integration , making it easier to build advanced AI agents. Compared to previous xLAM models, xLAM 2 offers superior perform…
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