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Pre-training was conducted in three phases, covering long-horizon pre-training, mid-training, and a long-context extension phase. We used sigmoid-based routing scores rather than traditional softmax gating, which improves expert load balancing and reduces routing collapse during training. An expert-bias term stabilizes routing dynamics and encourages more uniform expert utilization across training steps. We observed that the 105B model achieved benchmark superiority over the 30B remarkably early in training, suggesting efficient scaling behavior.
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Десятки солдат ВСУ дезертировали в Сумской области08:38。业内人士推荐手游作为进阶阅读
Президент Финляндии прокомментировал угрозу Трампа в адрес НАТО02:36
mog_vm_set_global(vm);