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LLM FundamentalsmediumMultiple ChoiceObjective-mapped

1Z0-1127-25 LLM Fundamentals Practice Question

A developer is using the Cohere Command model for text generation and wants to ensure the output is deterministic for testing purposes. Which sampling strategy should they use?

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

Greedy decoding

Greedy decoding always selects the token with highest probability, producing the same output for a given input. Temperature, top-k, and top-p introduce randomness.

Answer analysis

Option-by-option breakdown

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

  • Top-k sampling with k=50

    Why it's wrong here

    Top-k sampling includes randomness by sampling from the top k tokens.

  • Temperature sampling with temperature=0.7

    Why it's wrong here

    Temperature sampling is stochastic; even with low temperature, outputs can vary.

  • Top-p (nucleus) sampling with p=0.9

    Why it's wrong here

    Top-p sampling also introduces randomness by sampling from the top probability mass.

  • Greedy decoding

    Why this is correct

    Greedy decoding picks the most likely token at each step, making outputs deterministic.

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