AWS Certified AI Practitioner (AIF-C01) — Question 270

A company is working on a large language model (LLM) and noticed that the LLM’s outputs are not as diverse as expected.

Which parameter should the company adjust?

Answer options

• A. Temperature
• B. Batch size
• C. Learning rate
• D. Optimizer type

Correct answer: A

Explanation

Adjusting the Temperature parameter controls the randomness of the model's predictions, where higher values increase the diversity and creativity of the generated text. Other parameters like Batch size, Learning rate, and Optimizer type are used during the training phase to control training stability and convergence, rather than directly influencing output diversity at inference time.