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Today's tutorial focuses on fine-tuning a model in GPT-3, acknowledging its importance despite the potential complexity. The goal is to ensure consistent, desired outputs by creating a good prompt and utilizing data for fine-tuning. Consistency in output format, such as length and structure, is crucial when running the model. Fine-tuning is essential for achieving reliable and high-quality results.