We could just delete this assertion. Or we could just set the model to eval mode. Contrary to the name, it has nothing to do with whether the model is trainable or not. Eval mode just turns off train time behavior. Historically, this meant no dropout and using stored batch norm statistics rather than per-batch statistics. With modern LLM’s, this means, well, nothing—there typically are no train time specific behaviors. requires_grad controls whether gradients are tracked and only the parameters passed to the optimizer are updated.
Что думаешь? Оцени!，更多细节参见新收录的资料
据第一财经报道，今年汽车行业正面临新一轮存储芯片涨价潮，车规级 DRAM 与 NAND Flash 价格持续攀升，带动整车成本上扬，部分车型已出现终端售价上涨迹象。，这一点在新收录的资料中也有详细论述
even supposed to move PyObjects in memory, just use pointers - but