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Today's tutorial focuses on fine-tuning a model in GPT-3. The video may be longer than usual, but it is essential for understanding the implications of large language models in the future. To fine-tune a model, it is necessary to create a consistent output that meets specific criteria every time. This involves using a good prompt and ensuring the output has the desired format and structure. Fine-tuning requires data to train the model effectively.
