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Navigating Fine-Tuning Challenges in AI Models
This chapter explores the evolving practices of fine-tuning models, emphasizing gradient descent and innovative frameworks like Unsloth. It discusses overcoming practical challenges in specialized syntax and the advantages of structured versus unstructured outputs, particularly in classification tasks. The conversation highlights the importance of order and format in AI reasoning, along with the future implications for structured output generation in natural language processing.