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Accelerating Dropless MoE Training in JAX with NVIDIA Transformer Engine

Accelerating Dropless MoE Training in JAX with NVIDIA Transformer Engine

二〇二六年九月十四日 · 英文原文

Mixture of experts (MoE) has become one of the defining architectural trends in large-scale AI model training. DeepSeek, Qwen, and Mixtral are examples of MoE... Mixture of experts (MoE) has become one of the defining architectural trends in large-scale AI model training.…

Mixture of experts (MoE) has become one of the defining architectural trends in large-scale AI model training. DeepSeek, Qwen, and Mixtral are examples of MoE... Mixture of experts (MoE) has become one of the defining architectural trends in large-scale AI model training. DeepSeek, Qwen, and Mixtral are examples of MoE models that match or exceed the performance of dense model counterparts at a fraction of the training compute. MoE models provide efficient training through conditional computation. Instead of one dense feed-forward network (FFN) shared… Source

译自 NVIDIA · Developer 博客 · 录于 二〇二六年九月十四日