Rohan Paul Describes Handoff Tax for Model Switching
Machine learning engineer highlights performance issues when changing models during a run.
TLDR
Rohan Paul, a Bengaluru-based machine learning engineer and Kaggle Master, posted on X that model switching mid-run carries a handoff tax. He observed that stronger models often perform better when given less of the history produced by a weaker model. The statement appears in a retweet of his own post and forms part of visible discussion among AI practitioners on the platform.
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