Oct 1, 2024 · Model distillation involves fine-tuning smaller, cost-efficient models using outputs from more capable models, allowing them to match the performance of advanced models on …

Jan 30, 2025 · Overview of Distillation in Azure OpenAI Service. Azure OpenAI Service distillation involves three main components: Stored Completions: Easily generate datasets for distillation by capturing and storing input-output pairs from models like GPT-4o through our API. This allows you to build datasets with your production data for evaluating and fine ...

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Nov 19, 2024 · We're excited to introduce our upcoming release of Model Distillation feature in Azure OpenAI Service. This feature provides developers with a seamless, integrated workflow to manage the entire distillation pipeline directly within the Azure OpenAI platform.

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Oct 8, 2024 · Learn how to distill LLMs with OpenAI's distillation tool. This tutorial provides a step-by-step guide using GPT-4o and GPT-4o-mini for generating Git commands.

Oct 16, 2024 · OpenAI recently released Distillation which allows to leverage the outputs of a (large) model to fine-tune another (smaller) model. This can significantly reduce the price and the latency for specific tasks as you move to a smaller model.

Oct 1, 2024 · Distillation allows you to turn your stored completions into a fine-tuning dataset. A common use case is to use stored completions with a larger more powerful model for a particular task and then use the stored completions to train a smaller model on high quality examples of model interactions.

Oct 2, 2024 · We’re introducing a new Model Distillation workflow. Use outputs from larger models like GPT-4 or o1-preview to train smaller, cost-efficient models that deliver similar performance on specific tasks at a lower cost. This suite includes Stored Completions and Evals, now integrated directly in the OpenAI platform. Get started with our docs.

Nov 24, 2024 · Many of you are already performing distillation on your own, but it is complex. We’re introducing a new Model Distillation workflow. Use outputs from larger models like GPT-4 or o1-preview to train smaller, cost-efficient models that …