A $500 RL fine-tune of a 9B open model beat frontier models on catalog review
ai
Hacker News is reporting on an experiment where a five-hundred-dollar reinforcement learning fine-tune of a nine billion parameter open model beat frontier models on catalog review tasks. The result indicates that targeted training can match the performance of systems built with vastly greater resources.
Source: https://fermisense.com/when-machines-take-the-wheel/
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