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Today's tutorial focuses on fine-tuning a model in GPT-3, with an emphasis on creating a consistent output that meets certain criteria. The process involves creating a desired output with a good prompt and using data for fine-tuning. The goal is to ensure a consistent format and structure of the text output every time the model is run. This tutorial may be longer than usual but is essential for those interested in large language models and their implications in the future.
