Enhancing AI Model’s Scalability and Performance: A Study on Multi-Head Mixture-of-Experts

Large capacity models, such as Large Language Models (LLMs) and Large Multi-modal Models (LMMs), have demonstrated effectiveness across various domains and tasks. Scaling up these models by increasing parameter count enhances performance but significantly reduces inference speed, limiting practicality. Sparse Mixtures of Experts (SMoE) offer a promising alternative, enabling model scalability while mitigating computational costs. […]

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