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Improving Data-Constrained Scaling with Hyperparameter Transfer and Ensembling
As growing compute budgets outpace the growth of high-quality training data, large language models must be trained with both compute and data constraints in mind. Unfortunately, existing prescriptions for data-constrained scaling suffer from two important limitations. First, past works hold key hype
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