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1z0-1127-25 Exam Dumps - Oracle Cloud Infrastructure Questions and Answers

Question # 4

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

Options:

A.

Increasing temperature removes the impact of the most likely word.

B.

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

C.

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

D.

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

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Question # 5

Which is a characteristic of T-Few fine-tuning for Large Language Models (LLMs)?

Options:

A.

It updates all the weights of the model uniformly.

B.

It does not update any weights but restructures the model architecture.

C.

It selectively updates only a fraction of the model’s weights.

D.

It increases the training time as compared to Vanilla fine-tuning.

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Question # 6

What is the purpose of frequency penalties in language model outputs?

Options:

A.

To ensure that tokens that appear frequently are used more often

B.

To penalize tokens that have already appeared, based on the number of times they have been used

C.

To reward the tokens that have never appeared in the text

D.

To randomly penalize some tokens to increase the diversity of the text

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Question # 7

Which technique involves prompting the Large Language Model (LLM) to emit intermediate reasoning steps as part of its response?

Options:

A.

Step-Back Prompting

B.

Chain-of-Thought

C.

Least-to-Most Prompting

D.

In-Context Learning

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Question # 8

Which statement describes the difference between "Top k" and "Top p" in selecting the next token in the OCI Generative AI Generation models?

Options:

A.

"Top k" and "Top p" are identical in their approach to token selection but differ in their application of penalties to tokens.

B.

"Top k" selects the next token based on its position in the list of probable tokens, whereas "Top p" selects based on the cumulative probability of the top tokens.

C.

"Top k" considers the sum of probabilities of the top tokens, whereas "Top p" selects from the "Top k" tokens sorted by probability.

D.

"Top k" and "Top p" both select from the same set of tokens but use different methods to prioritize them based on frequency.

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Question # 9

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

Options:

A.

Providing the exact k words in the prompt to guide the model's response

B.

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

C.

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

D.

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

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Question # 10

How does a presence penalty function in language model generation?

Options:

A.

It penalizes all tokens equally, regardless of how often they have appeared.

B.

It penalizes only tokens that have never appeared in the text before.

C.

It applies a penalty only if the token has appeared more than twice.

D.

It penalizes a token each time it appears after the first occurrence.

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Question # 11

Given the following code:

PromptTemplate(input_variables=["human_input", "city"], template=template)

Which statement is true about PromptTemplate in relation to input_variables?

Options:

A.

PromptTemplate requires a minimum of two variables to function properly.

B.

PromptTemplate can support only a single variable at a time.

C.

PromptTemplate supports any number of variables, including the possibility of having none.

D.

PromptTemplate is unable to use any variables.

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Question # 12

Given the following prompts used with a Large Language Model, classify each as employing the Chain-of-Thought, Least-to-Most, or Step-Back prompting technique:

Options:

A.

"Calculate the total number of wheels needed for 3 cars. Cars have 4 wheels each. Then, use the total number of wheels to determine how many sets of wheels we can buy with $200 if one set (4 wheels) costs $50."

B.

"Solve a complex math problem by first identifying the formula needed, and then solve a simpler version of the problem before tackling the full question."

C.

"To understand the impact of greenhouse gases on climate change, let’s start by defining what greenhouse gases are. Next, we’ll explore how they trap heat in the Earth’s atmosphere."A. 1: Step-Back, 2: Chain-of-Thought, 3: Least-to-MostB. 1: Least-to-Most, 2: Chain-of-Thought, 3: Step-BackC. 1: Chain-of-Thought, 2: Step-Back, 3: Least-to-MostD. 1: Chain-of-Thought, 2: Least-to-Most, 3: Step-Back

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Question # 13

What distinguishes the Cohere Embed v3 model from its predecessor in the OCI Generative AI service?

Options:

A.

Support for tokenizing longer sentences

B.

Improved retrievals for Retrieval Augmented Generation (RAG) systems

C.

Emphasis on syntactic clustering of word embeddings

D.

Capacity to translate text in over 100 languages

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Exam Code: 1z0-1127-25
Exam Name: Oracle Cloud Infrastructure 2025 Generative AI Professional
Last Update: Mar 29, 2025
Questions: 88
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