Last week we released NanoGPT Slowrun , an open repo for data-efficient learning algorithms. The rules are simple: train on 100M tokens from FineWeb, use as much compute as you want, lowest validation loss wins. Improvements are submitted as PRs to the repo and merged if they lower val loss. The constraint is the inverse of speedruns like modded-nanogpt , which optimize wall-clock time. Those benchmarks have been hugely productive, but optimizing for speed filters out expensive ideas: heavy regularization, second-order optimizers, gradient descent alternatives. Slowrun is built for exactly those ideas.
Солнце выбросило гигантский протуберанец размером около миллиона километров02:48
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Ранее в сети опубликовали архивные кадры разговора летчика ВСУ с российским бойцом под Киевом, снятое в первые дни специальной военной операции.
Trump threatens to cut trade with ‘terrible’ Spain and calls Starmer ‘no Churchill’
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