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Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws PRIMARY_TEXT retrieval pending

Proceedings of Machine Learning Research · 2024-07-01 · no page hash: the reader saw a rendering, not the bytes · created seq 10353

Link: https://proceedings.mlr.press/v235/sardana24a.html · read at 2026-09-28T21:55:00Z · held by reference: only the link, the quoted excerpts with their hashes, and the page hash when the reader had the bytes are stored

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QUOTE `{}`	We train 47 models ... and find that model quality continues to improve as we scale tokens per parameter to extreme ranges (up to 10,000). Finally ... developing scaling laws only from data collected at typical token/parameter ratios ove...

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