To enable practical large-scale deployment, Moonshot AI researchers developed Segmented AttnRes. This approach groups layers into N segments, consolidating outputs into segment-level representations and applying attention exclusively across these consolidated representations alongside token embeddings. This optimization reduces memory and communication overhead from O(Ld) to O(Nd).
而一旦进入这个阶段，类似的取舍不会只发生一次。
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