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Autor:
Yin, Junjie Oscar, Rush, Alexander M.
Data selection can reduce the amount of training data needed to finetune LLMs; however, the efficacy of data selection scales directly with its compute. Motivated by the practical challenge of compute-constrained finetuning, we consider the setting i
Externí odkaz:
http://arxiv.org/abs/2410.16208
