Oracle 1Z0-1127-24 Exam Questions - Real Practice Questions for Guaranteed Success

Question 1

How does the Retrieval-Augmented Generation (RAG) Token technique differ from RAG Sequence when generating a model's response?

AUnlike RAG Sequence, RAG Token generates the entire response at once without considering individual parts.

BRAG Token does not use document retrieval but generates responses based on pre-existing knowledge only.

CRAG Token retrieves documents oar/at the beginning of the response generation and uses those for the entire content

DRAG Token retrieves relevant documents for each part of the response and constructs the answer incrementally.

Correct : C

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AUnlike RAG Sequence, RAG Token generates the entire response at once without considering individual parts.

BRAG Token does not use document retrieval but generates responses based on pre-existing knowledge only.

CRAG Token retrieves documents oar/at the beginning of the response generation and uses those for the entire content

DRAG Token retrieves relevant documents for each part of the response and constructs the answer incrementally.

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Question 2

Which component of Retrieval-Augmented Generation (RAG) evaluates and prioritizes the information retrieved by the retrieval system?

ARetriever

BEncoder-decoder

CRanker

DGenerator

Correct : C

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ARetriever

BEncoder-decoder

CRanker

DGenerator

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Question 3

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

ATop 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 token.

BTop K considers the sum of probabilities of the top tokens, whereas Top' selects from the Top k' tokens sorted by probability.

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

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

Correct : B

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ATop 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 token.

BTop K considers the sum of probabilities of the top tokens, whereas Top' selects from the Top k' tokens sorted by probability.

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

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

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Question 4

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

ATop p assigns penalties to frequently occurring tokens.

BTop p determines the maximum number of tokens per response.

CTop p limits token selection based on the sum of their probabilities.

DTop p selects tokens from the ''Top k' tokens sorted by probability.

Correct : C

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ATop p assigns penalties to frequently occurring tokens.

BTop p determines the maximum number of tokens per response.

CTop p limits token selection based on the sum of their probabilities.

DTop p selects tokens from the ''Top k' tokens sorted by probability.

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Question 5

What does "Loss" measure in the evaluation of OCI Generative AI fine-tuned models?

The difference between the accuracy of the model at the beginning of training and the accuracy of the deployed model

AThe difference between the accuracy of the model at the beginning of training and the accuracy of the deployed model

BThe percentage of incorrect predictions made by the model compared with the total number of predictions in the evaluation

CThe improvement in accuracy achieved by the model during training on the user-uploaded data set

DThe level of incorrectness in the models predictions, with lower values indicating better performance

Correct : D

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AThe difference between the accuracy of the model at the beginning of training and the accuracy of the deployed model

BThe percentage of incorrect predictions made by the model compared with the total number of predictions in the evaluation

CThe improvement in accuracy achieved by the model during training on the user-uploaded data set

DThe level of incorrectness in the models predictions, with lower values indicating better performance

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Master Oracle 1Z0-1127-24 Exam with Reliable Practice Questions

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