Enhancing Efficiency and Performance for Fine-Tuning with Distillation in Azure OpenAI Service

Model distillation empowers developers to use the outputs of large, complex models to fine-tune smaller, more efficient ones. This technique allows the smaller models to perform just as well on specific tasks, all while significantly cutting down on both cost and latency. Azure OpenAI Service creates a comprehensive distillation process: collecting live traffic from Azure OpenAI endpoints, filtering and subletting that traffic in the Stored Completions UI, exporting it to the Evaluation UI for quality scoring, and finally, fine-tuning from the collected data or a subset based on evaluation scoring.

Learn more: https://msft.it/6054U4Pdi

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