AIF-C01 · Question #96
A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. The company needs the LLM to produce more consistent responses to the same input prompt. Which…
The correct answer is A. Decrease the temperature value. The temperature parameter in a large language model (LLM) controls the randomness of the model's output. A lower temperature value makes the output more deterministic and consistent, meaning that the model is less likely to produce different results for the same input prompt.
Question
A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. The company needs the LLM to produce more consistent responses to the same input prompt. Which adjustment to an inference parameter should the company make to meet these requirements?
Options
- ADecrease the temperature value
- BIncrease the temperature value
- CDecrease the length of output tokens
- DIncrease the maximum generation length
How the community answered
(31 responses)- A68% (21)
- B10% (3)
- C19% (6)
- D3% (1)
Explanation
The temperature parameter in a large language model (LLM) controls the randomness of the model's output. A lower temperature value makes the output more deterministic and consistent, meaning that the model is less likely to produce different results for the same input prompt.
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