AWS Certified Cloud Practitioner
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A financial analytics company needs deterministic LLM outputs so that every run produces the same result given the same input. Which configuration is most appropriate?
Real Exam
Community
RRitesh
A
Temperature = 0.0
B
Top-p = 0.9
C
Temperature = 1.5
D
Top-k = 50
Explanation:
Explanation:
In Large Language Model (LLM) configurations:
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Temperature controls the randomness of predictions. A temperature of 0.0 makes the model completely deterministic, always selecting the highest probability token. This ensures the same input always produces the same output.
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Top-p (nucleus sampling) sets a cumulative probability threshold (e.g., 0.9 means considering tokens that make up 90% of the probability mass). This still allows for randomness.
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Temperature = 1.5 increases randomness, making outputs more creative and less predictable.
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Top-k limits the sampling pool to the k most likely tokens (e.g., 50 tokens), which still allows for variation.
For financial analytics requiring deterministic outputs, Temperature = 0.0 is the correct configuration as it eliminates randomness and ensures reproducibility.
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