xLAM

xLAM is a new series of action models designed specifically for AI tasks. It includes five different models, built using either dense or mixture-of-expert architectures. These models range in size from 1 billion to 8x22 billion parameters. A flexible and scalable training pipeline was used to enhance their performance across a variety of environments by combining and augmenting diverse datasets. Initial tests show that xLAM consistently performs well, placing first on the Berkeley Function-Calling Leaderboard and surpassing other prominent models like GPT-4 and Claude-3 in specific tasks, particularly those requiring tool use.