In this technical session, we will explore the process of fine-tuning base models in Azure OpenAI to create customized and optimized AI solutions. We will begin with a comparative overview of Retrieval-Augmented Generation (RAG) and fine-tuning techniques, highlighting their respective strengths and use cases. This foundation will set the stage for an in-depth examination of fine-tuning, covering critical concepts such as base models, the preparation of JSONL files, and the detailed tuning procedure.
Participants will gain insights into selecting the appropriate base model for their use case, formatting data correctly in JSONL files, and executing the fine-tuning process on Azure OpenAI. By the end of the session, attendees will be equipped with the knowledge and skills necessary to fine-tune OpenAI models effectively, enabling them to leverage advanced AI capabilities for their specific applications.