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

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

Correct Answer: C

In the simplified workflow for managing and querying vector data, what is the role of indexing?

1. A. To convert vectors into a non-indexed format for easier retrieval
2. B. To map vectors to a data structure for faster searching, enabling efficient retrieval
3. C. To compress vector data for minimized storage usage
4. D. To categorize vectors based on their originating data type (text, images, audio)

Correct Answer: B

What issue might arise from using small datasets with the Vanilla fine-tuning method in the OCI Generative AI service?

1. A. Overfitting
2. B. Underfitting
3. C. Data Leakage
4. D. Model Drift

Correct Answer: A

Which statement is true about string prompt templates and their capability regarding variables?

1. A. They can only support a single variable at a time.
2. B. They are unable to use any variables.
3. C. They support any number of variables, including the possibility of having none.
4. D. They require a minimum of two variables to function properly.

Correct Answer: C

What differentiates Semantic search from traditional keyword search?

1. A. It relies solely on matching exact keywords in the content.
2. B. It depends on the number of times keywords appear in the content.
3. C. It involves understanding the intent and context of the search.
4. D. It is based on the date and author of the content.

Correct Answer: C