Exams / AIF-C01 / Choosing FMs and inference parameters / Question 1
AIF-C01 practice question: Choosing FMs and inference parameters (1 of 4)
Applications of Foundation Models A free question from our original AIF-C01 practice exam. Try it, then open the answer to see why each option is right or wrong.
An insurance company's assistant answers questions about policy wording. Compliance wants answers to be as consistent and focused as possible, with little creative variation. Which inference parameter change helps MOST?
Choose one answer.
- AA. Raise the temperature so the model explores more options
- BB. Raise the maximum response length so answers are complete
- CC. Lower the temperature so the model favours likely tokens
- DD. Add a stop sequence so the model stops after each sentence
Show the answer and explanation
Answer: C
- A. Wrong: A higher temperature flattens the probability distribution and makes responses more random, which is the opposite of what compliance wants.
- B. Wrong: Response length controls how many tokens are returned. It does not make the content more consistent.
- C. Right: Correct. A lower temperature makes the model pick higher-probability tokens, giving more deterministic, focused output.
- D. Wrong: A stop sequence ends generation at a given string. It shortens answers but does not reduce randomness.
Explanation
Temperature shapes the probability distribution the model samples from. Low values make output more predictable and focused, which suits factual or regulated use cases. High values make output more varied and creative, which suits brainstorming or marketing copy.
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