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Scaling laws don't care about scale of the "train" models? Did anyone else get this? When I predict a scaling law, the scale of the largest model matters, but the num-models for fitting matters much much much more. Initial results, scaling error by #models starting from largest https://twitter.com/LChoshen/status/1803401845626511568/photo/1 Maybe more simply put: You can predict a scaling law with 8 small models, and it would be better than 3 large ones (that costs a lot) Is that something anyone else seen?

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