Трамп высказался о сроках войны с Ираном01:42
"noaux_tc" is the only topk_method available. Why can't we put it in train mode? Well, this implementation of the MoEGate isn't differentiable. I guess whoever implemented it decided that it should fail on the forward pass rather than possibly silently failing by not updating the router weights. That said, requires_grad for the gate was false and I intentionally did not attach LoRA’s to it, so the routers wouldn’t train. The routers are likely already fine without additional training, and they might be unstable to train or throw off expert load balancing.
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Even the simplest systems can become unpredictable with time because, while the past may indeed predict the future, the approximate past does not. This is chaos. Measurements with real instruments in the real world are always imprecise and so lead to unremovable error. These errors stack up over time and eventually reduce the usefulness of our models.