Guide
What is Fine-Tuning?
Customizing LLMs for specific tasks and domains.
Fine-tuning adapts a pre-trained LLM to specific tasks by training on domain-specific data. It changes model weights to improve performance on your use case.
When to Fine-Tune
- Specific output format or style needed
- Domain-specific terminology
- Consistent behavior patterns
- Prompting alone isn't sufficient
Fine-Tuning vs Alternatives
- Prompting: Fastest, no training needed
- RAG: Add knowledge without retraining
- Fine-tuning: Change model behavior fundamentally
Does fine-tuning prevent hallucinations?
Not necessarily. Fine-tuned models can still hallucinate. Production monitoring remains essential.
Monitor fine-tuned models
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