You now understand when fine-tuning makes sense and when other approaches work better.
Key takeaways:
- Always try prompting first
- Use RAG for knowledge, fine-tuning for behavior
- Quality data matters more than quantity
- Define success metrics before starting
- Plan for ongoing maintenance
Next, I'll teach you how transformers work under the hood so you understand what you're fine-tuning.