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大模型“炼丹”容易“修仙”难:猎户星空跨越AI应用鸿沟|甲子光年
相较于传统的dense(稠密)模型,MoE模型通过采用专家网络的稀疏激活机制,显著减少了每次前向传播所需的计算量,可以有效加快训练速度、降低运行延迟;由于每次只激活一小部分专家进行工作,MoE模型实际上使用的参数量远少于同等规模的稠密模型,可以用更少 ...
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