Should you train your own model? Usually, the answer is no.
Prompt Engineering (Context)
Best for: Giving the model new information (RAG) or instructions.
- Pros: Instant, free, flexible.
- Cons: Limited by context window size.
Fine-Tuning (Training)
Best for: Changing the behavior or style of the model.
- Example: Making the model speak like a pirate permanently.
- Example: Teaching the model a new medical classification format.
- Pros: Permanent behavior change, no need for long prompts.
- Cons: Expensive (requires GPU time), difficult to get right, can cause 'catastrophic forgetting'.
Verdict
Try RAG (Retrieval Augmented Generation) first. Only fine-tune if RAG fails to capture the specific style or format you need. If the task is choosing among fixed labels, try an open decision model instead of fine-tuning a chat model, and measure it on your own labelled examples first.