1Z0-1127-25 OCI Generative AI Service Practice Question
A developer is using the OCI Generative AI Playground to test a Cohere Command R model. They want to reduce repetitiveness in the generated responses. Which parameter should they increase?
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
✓
Frequency penalty
Frequency penalty penalizes tokens that have already appeared in the text, reducing repetition. Temperature increases randomness, top_p changes nucleus sampling, and max tokens controls length.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Max tokens
Why it's wrong here
Max tokens limits output length, but does not affect repetition.
- ✗
Top P
Why it's wrong here
Top P controls nucleus sampling, not repetition.
- ✓
Frequency penalty
Why this is correct
A higher frequency penalty discourages the model from repeating the same tokens.
- ✗
Temperature
Why it's wrong here
Temperature controls randomness, not repetition directly.
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