Choosing and Tuning¶
Which model should this task use? Answer the eligibility gates first, compare families by what they're built for, run your own small bake-off — and only climb the prompt → examples → RAG → fine-tune ladder when the rung below fails.
flowchart LR
J["Junior: gates + family fit"] --> M["Middle: bake-offs + the ladder"]
M --> S["Senior: fine-tuning for real"]
S --> P["Professional: multi-model strategy"]
Levels¶
| Level | Guide | You are done when |
|---|---|---|
| Junior | Gates and family fit | You can run the eligibility checklist and match a task to a model family by design intent. |
| Middle | Bake-offs and the ladder | You can run a small comparison on your own cases and know when each ladder rung is justified. |
| Senior | Fine-tuning for real | You can judge when fine-tuning is right, prepare its data, and measure success with the right metrics. |
| Professional | Multi-model strategy | You can set a model strategy that limits lock-in and handles new releases and retirements. |
Practice rule¶
Leaderboard deltas are not evidence for your task. Ten real cases from your own data, graded against your own bar, beat any public benchmark comparison.
Related¶
- How LLMs Work — what parameters, distillation, and hosted-vs-open-weight mean for the choice.
- Temperature and Sampling — the settings that must travel with any model switch.