Microsoft Azure (legacy) — Question 12

Which statement accurately describes the difference between a pretrained generative AI model and a fine-tuned generative AI model?

Answer options

• A. A pretrained model requires labeled data, while a fine-tuned model does not.
• B. A pretrained model is faster to train than a fine-tuned model because the pretrained model uses fewer parameters.
• C. A pretrained model is trained on broad datasets, while a fine-tuned model is adapted to perform well on a narrower, domain-specific dataset.
• D. A pretrained model is optimized for a specific task, while a fine-tuned model is designed for general-purpose use.

Correct answer: C

Explanation

The correct answer is C because a pretrained model is typically trained on large and diverse datasets, while a fine-tuned model takes that pretrained knowledge and adjusts it for specific tasks or narrower datasets. The other options incorrectly describe the training requirements and purposes of these models, such as suggesting that pretrained models require labeled data or are optimized for specific tasks.