1Z0-1127-25 OCI Generative AI Service Practice Question
A data scientist is using the OCI Generative AI Playground to test a summarization model. They want to generate shorter summaries and avoid repetitive phrasing. Which parameter adjustments should they make?
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
✓
Decrease temperature and increase frequency penalty
Lowering temperature reduces randomness, increasing frequency penalty penalizes repeated tokens, and setting appropriate max tokens controls output length. Stop sequences define when generation stops, and presence penalty penalizes token presence overall.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Decrease temperature and increase frequency penalty
Why this is correct
Lower temperature makes output more deterministic (focused summaries), and higher frequency penalty discourages repetition, achieving the goal.
- ✗
Increase temperature and increase presence penalty
Why it's wrong here
Increasing temperature can produce more diverse but less concise summaries; presence penalty reduces repetition but may not ensure shorter length.
- ✗
Set stop sequences and disable frequency penalty
Why it's wrong here
Stop sequences control when generation ends but do not directly shorten summaries; disabling frequency penalty may increase repetition.
- ✗
Increase temperature and decrease frequency penalty
Why it's wrong here
Increasing temperature increases randomness, which may lead to less consistent summaries. Decreasing frequency penalty may increase repetition.
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