Question 1

What is the primary function of the "temperature" parameter in the OCI Generative AI Generation models?

Options :

A : Specifies a string that tells the model to stop generating more content

B : Determines the maximum number of tokens the model can generate per response

C : Controls the randomness of the model’s output, affecting its creativity

D : Assigns a penalty to tokens that have already appeared in the preceding text

Answer: C

Question 2

How does the temperature setting in a decoding algorithm influence the probability distribution over the vocabulary?

Options :

A : Increasing the temperature flattens the distribution, allowing for more varied word choices.

B : Increasing the temperature removes the impact of the most likely word.

C : Temperature has no effect on probability distribution; it only changes the speed of decoding.

D : Decreasing the temperature broadens the distribution, making less likely words more probable.

Answer: A

Question 3

What differentiates a code model from a standard LLM?

Options :

A : Code models are specifically designed to generate different creative text formats.

B : Code models are trained on datasets containing code alongside natural language.

C : Code models require a different neural network architecture compared to LLMs.

D : Code models can only process and understand code, not natural language.

Answer: B

Question 4

When considering access control for OCI Generative AI resources, what role does IAM play?

Options :

A : IAM provides built-in security policies for all Generative AI functionalities.

B : IAM allows defining granular access permissions for users and groups.

C : IAM automatically authenticates users interacting with the Generative AI service.

D : IAM encrypts data at rest within the OCI Generative AI environment.

Answer: B

Question 5

What does "k-shot prompting" refer to when using Large Language Models for task-specific applications?

Options :

A : Explicitly providing k examples of the intended task in the prompt to guide the model’s output

B : Limiting the model to only k possible outcomes or answers for a given task

C : Providing the exact k words in the prompt to guide the model’s response

D : The process of training the model on k different tasks simultaneously to improve its versatility

Answer: A