Question 1

How can fine-tuning an LLM model with OCI Generative AI contribute to improved performance of semantic search in your application?

Options :

A : By enabling the LLM to directly generate documents based on semantic similarity.

B : By allowing the LLM to interpret the retrieved documents and provide more context-aware responses.

C : By improving the accuracy of vector representations generated for the documents in the database.

D : By optimizing the search algorithms used by the vector database for specific LLM tasks.

Answer: B

Question 2

What is the role of temperature in the decoding process of a Large Language Model (LLM)?

Options :

A : To increase the accuracy of the most likely word in the vocabulary

B : To determine the number of words to generate in a single decoding step

C : To decide to which part of speech the next word should belong

D : To adjust the sharpness of probability distribution over vocabulary when selecting the next word

Answer: D

Question 3

When considering security best practices for model endpoints in OCI Generative AI, which approach is most recommended?

Options :

A : Leaving endpoints publicly accessible for ease of experimentation.

B : Restricting access with IAM policies and requiring authentication tokens.

C : Granting full access permissions to all users within your organization.

D : Disabling monitoring for deployed endpoints to minimize resource cons

Answer: B

Question 4

When using the OCI Generative AI service playground, which of the following functionalities is NOT available?

Options :

A : Experimenting with pre-trained models for text generation and summarization.

B : Training a custom LLM from scratch on your uploaded dataset.

C : Fine-tuning a pre-trained model with a small amount of data using T-Few.

D : Deploying a fine-tuned model as an endpoint for real-world applicatio

Answer: B

Question 5

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

Options :

A : Because text generation does not require complex models

B : Because text is not categorical

C : Because text representation is categorical unlike images

Answer: C

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