Online 1Z0-1127-25 Practice Test

Question 1

How does the integration of a vector database into Retrieval-Augmented Generation (RAG)-based Large Language Models (LLMs) fundamentally alter their responses?

Options :

A : It transforms their architecture from a neural network to a traditional database system.

B : It shifts the basis of their responses from pretrained internal knowledge to real-time data retrieval.

C : It enables them to bypass the need for pretraining on large text corpora.

D : It limits their ability to understand and generate natural language.

Answer: B

Question 2

In the context of fine-tuning with OCI Generative AI Service, what is the role of a custom dataset?

Options :

A : It defines the new tasks the model should be able to perform.

B : It provides additional training data specific to your domain.

C : It acts as a validation set to evaluate the fine-tuned model-s performance.

D : It replaces the pre-trained weights of the base model entirely.

Answer: B

Question 3

Given the following code: Prompt Template (input_variable[‘’rhuman_input",'city’’], template-template) Which statement is true about Promt Template in relation to input_variables?

Options :

A :

PromptTemplate requires a minimum of two variables to function property.

B :

PromptTemplate can support only a single variable M a time.

C :

PromptTemplate supports Any number of variable*, including the possibility of having none.

D :

PromptTemplate is unable to use any variables.

Answer: C

Question 4

What does the Loss metric indicate about a model's predictions?

Options :

A : Loss is a measure that indicates how wrong the model-s predictions are.

B : Loss measures the total number of predictions made by a model.

C : Loss describes the accuracy of the right predictions rather than the incorrect ones.

D : Loss indicates how good a prediction is, and it should increase as the model improves.

Answer: A

Question 5

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

EXPERTY DESIGNED 1Z0-1127-25 PRACTICE TEST