A municipal snow-fence request shop may later train a model on last year’s fence-map cases so wording matches house sheets. Which selection criterion does that future option represent?
Select an answer to reveal the explanation.
Short Explanation
Sometimes the house dialect matters more than the stock voice. Fine-tuning potential asks whether the team can usefully adapt the model with domain-specific data such as last year’s fence-map cases. That is a selection criterion, not a full training-job how-to.
Full Explanation
LLM/SLM selection includes fine-tuning potential: whether it is possible and useful to fine-tune with domain-specific data so outputs better match house materials. How fine-tuning works is covered elsewhere; here the criterion is the option to adapt later. Discovery access, transparency stamps, and Chapter 3 compliance instruments are different syllabus topics.