Definition
Fine-tuning is the process of taking a pre-trained model and training it further on a smaller, task-specific dataset to improve its performance on that particular task.
Why Fine-Tune? - Pre-trained models are general-purpose - Fine-tuning specializes them for your use case - Requires less data than training from scratch - Faster and cheaper than full training
- **Common Approaches:**
- Full Fine-Tuning: Update all model weights
- LoRA: Low-Rank Adaptation - update only small adapter layers
- RLHF: Reinforcement Learning from Human Feedback
Examples
Fine-tuning GPT on customer service conversations to create a support chatbot.
Related Terms
The process of teaching an AI model to perform tasks by exposing it to data.
Training method using human preferences to make AI more helpful and safe.
Efficient fine-tuning technique that trains small adapter modules instead of full models.
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