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Oracle Cloud Infrastructure 2025 Generative AI Professional Sample Questions:

1. Why is it challenging to apply diffusion models to text generation?

A) Because text is not categorical
B) Because diffusion models can only produce images
C) Because text generation does not require complex models
D) Because text representation is categorical unlike images

2. How are fine-tuned customer models stored to enable strong data privacy and security in the OCI Generative AI service?

A) Shared among multiple customers for efficiency
B) Stored in Object Storage encrypted by default
C) Stored in an unencrypted form in Object Storage
D) Stored in Key Management service

3. Which statement is true about the "Top p" parameter of the OCI Generative AI Generation models?

A) "Top p" determines the maximum number of tokens per response.
B) "Top p" selects tokens from the "Top k" tokens sorted by probability.
C) "Top p" assigns penalties to frequently occurring tokens.
D) "Top p" limits token selection based on the sum of their probabilities.

4. Which is a key advantage of using T-Few over Vanilla fine-tuning in the OCI Generative AI service?

A) Increased model interpretability
B) Reduced model complexity
C) Enhanced generalization to unseen data
D) Faster training time and lower cost

5. In which scenario is soft prompting appropriate compared to other training styles?

A) When the model needs to be adapted to perform well in a domain on which it was not originally trained
B) When the model requires continued pretraining on unlabeled data
C) When there is a significant amount of labeled, task-specific data available
D) When there is a need to add learnable parameters to a Large Language Model (LLM) without task-specific training

Solutions: