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FP8 for lm_head：这是一个反直觉的结果。虽然通常认为量化能省显存，但在 Karpathy 的代码里，FP8 反而导致显存增加了 2GB，且训练速度仅提升 1%。考虑到实现的复杂度，投入产出比极低。