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In this tutorial, we will explore how to fine-tune a model in GPT-3. The video may be longer than usual, but it is necessary as there are implications in large language models in the future. To start, we need to create a desired output using a good prompt. Fine-tuning aims to create consistent output that meets specific criteria every time. This can include the length and structure of the text. Data is essential for fine-tuning, so we will address this in the tutorial despite the presenter being a bit sick.
