Lesson deck
Fine-tuning vs RAG vs prompting flashcards
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- Front
- When is fine-tuning the right choice over RAG?
- Back
- When you need consistent style, format or behaviour at scale, have labelled examples, and prompting has hit its limit. Not for injecting facts or current knowledge.
- Front
- Does fine-tuning fix hallucination?
- Back
- Not by itself. It does not supply correct facts, and one 2024 study found hallucination rose as new facts were absorbed. Training on correct refusals can improve abstention (R-Tuning, NAACL 2024). Facts still need grounding via RAG.
- Front
- What does each lever change: prompting, RAG, fine-tuning?
- Back
- Prompting changes the instructions. RAG changes the information in the prompt at answer time. Fine-tuning changes the weights, to teach a consistent pattern of behaviour.
- Front
- Three things fine-tuning does poorly compared with RAG?
- Back
- Keeping facts current (needs retraining), giving citations (no source passage), and per-user access control (weights are shared by every user).
- Front
- What must exist before you start a fine-tune?
- Back
- Labelled examples, a strong baseline (best prompt, plus RAG if facts matter), an eval with a held-out set, a reason prompting cannot meet, and a plan to retrain when the base model changes.