Mixture of Experts Explained
Key Takeaway: Mixture-of-experts (MoE) models enable more compute-efficient pretraining and faster inference compared to dense models, but face challenges with generalization during fine-tuning. Recent work on instruction tuning shows promise for improving MoE fine-tuning. MoEs replace the feedforward layers in transformers with sparse MoE layers composed of experts and a…