Muon outperforms every optimizer we tested (AdamW, SOAP, MAGMA). Multi-epoch training matters. And following work by Kotha et al. , scaling to large parameter counts works if you pair it with aggressive regularization -- weight decay up to 16x standard, plus dropout. The baseline sits at ~2.4x data efficiency against modded-nanogpt.
(Example code for implementing this below.)
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Just to emphasize once more, Infrastructure-Modules are optional. They make sense only when the module contains non-trivial business logic. In other cases, e.g. when designing CRUD-based modules, Infrastructure-Modules would be just a burden, and you should fall back to the classic Modular Design practices.，详情可参考快连下载-Letsvpn下载
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