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Fundamentals of Large Language ModelseasyMultiple ChoiceObjective-mapped

1Z0-1127-25 Fundamentals of Large Language Models Practice Question

A company wants to use OCI Generative AI to summarize customer reviews. Which model parameter should be adjusted to control the creativity of the summary?

⚠ Common exam trap

Oracle often tests the distinction between parameters that control randomness (temperature) versus those that control repetition (frequency/presence penalties) or sampling pool size (top-k), leading candidates to confuse diversity with creativity.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Temperature

Temperature controls the randomness of token selection in the model's output distribution. A higher temperature (e.g., 0.9) makes the summary more creative and diverse, while a lower temperature (e.g., 0.1) makes it more deterministic and focused. For summarizing customer reviews, adjusting temperature directly influences how novel or conservative the generated text will be.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Temperature

    Why this is correct

    Temperature directly controls randomness and creativity.

  • Frequency penalty

    Why it's wrong here

    Frequency penalty discourages repetition, not overall creativity.

  • Top-k

    Why it's wrong here

    Top-k limits the number of tokens considered, affecting diversity but not creativity directly.

  • Presence penalty

    Why it's wrong here

    Presence penalty encourages new topics, but temperature is the primary control for creativity.

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