A distilled model is a compact AI that mimics a larger model's behavior with minimal performance loss. It is used to deploy efficient machine learning solutions on edge devices like smartphones or IoT hardware. Developers, startups, and enterprises benefit from faster inference, lower costs, and reduced computational demands without sacrificing accuracy.
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