Moe (2) 썸네일형 리스트형 [MoH 논문 리뷰] - MULTI-HEAD ATTENTION AS MIXTURE-OF-HEAD ATTENTION *MoH를 위한 논문 리뷰 글입니다! 궁금하신 점은 댓글로 남겨주세요! MoH paper: [2410.11842] MoH: Multi-Head Attention as Mixture-of-Head Attention (arxiv.org) MoH: Multi-Head Attention as Mixture-of-Head AttentionIn this work, we upgrade the multi-head attention mechanism, the core of the Transformer model, to improve efficiency while maintaining or surpassing the previous accuracy level. We show that multi-head attentio.. [MoE 논문 리뷰] - Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity *MoE를 위한 논문 리뷰 글입니다! 궁금하신 점은 댓글로 남겨주세요! MoE paper: https://arxiv.org/abs/2101.03961 Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity In deep learning, models typically reuse the same parameters for all inputs. Mixture of Experts (MoE) defies this and instead selects different parameters for each incoming example. The result is a sparsely-activated mode.. 이전 1 다음