AI / LLM Basics Interview Questions
What is Fine-Tuning?
Fine-tuning is the process of further training an already-pretrained model on a smaller, more specific dataset to adjust its behavior for a particular task or style.
- Starts from a pretrained base model rather than training from scratch
- Uses a much smaller, more targeted dataset than pretraining requires
- Can adapt a general-purpose model into one specialized for tasks like customer support, coding, or following conversational instructions
This two-stage approach, broad pretraining followed by targeted fine-tuning, is far more efficient than training a specialized model entirely from scratch for every new use case.
What does fine-tuning start from?
What kind of dataset does fine-tuning typically use compared to pretraining?
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