New language models are being developed to improve Natural Language Processing (NLP). These models, known as Mixture-of-Experts (MoE) models, are designed to be more efficient and powerful. OpenMoE is a comprehensive suite of MoE models with parameters ranging from 650 million to 34 billion. These models have been trained on a vast dataset and are now available to the public. Their development has been based on a deep understanding of MoE routing mechanisms, leading to more efficient task performance. OpenMoE’s performance evaluation has shown that these models are cost-effective and perform well against other models. This project marks a significant step toward creating more accessible and democratic NLP research. By sharing analyses, methodologies, and models, the team is fostering a more inclusive field. OpenMoE sets a new standard for the future development of language models, providing a solution and inspiration for the NLP community. 🚀 LLMWare Launches SLIMs: Small Specialized Function-Calling Models for Multi-Step Automation [Check out all the models]