Online 1Z0-1127-25 Practice Test

Question 1

What is a potential drawback of using RAG in OCI Generative AI applications?

Options :

A : RAG is computationally expensive due to the retrieval process.

B : RAG can only be used with specific pre-trained models offered by OCI.

C : RAG requires extensive training data for the Retriever component.

D : RAG outputs are limited to factual summaries and lack creativity.

Answer: A

Question 2

What does accuracy measure in the context of fine-tuning results for a generative model?

Options :

A : The depth of the neural network layers used in the model

B : The number of predictions a model makes, regardless of whether they are correct or incorrect

C : How many predictions the model made correctly out of all the predictions in an evaluation

D : The proportion of incorrect predictions made by the model during an evaluation

Answer: C

Question 3

Which is NOT a built-in memory type in LangChain?

Options :

A : ConversationImageMemory

B : ConversationBufferMemory

C : ConversationSummaryMemory

D : ConversationTokenBufferMemory

Answer: A

Question 4

Given the following code:

chain - prompt | 11m

Which statement is true about LangChain Expression Language (LCEL)?

Options :

A : LCEL is an older Python library for building Large Language Models.

B : LCEL is a declarative and preferred way to compose chains together.

C : LCEL is a programming language used to write documentation for LangChain.

D : LCEL is a legacy method for creating chains in LangChain.

Answer: B

Question 5

After successfully fine-tuning a model in OCI Generative AI, which option allows you to integrate the model into production applications?

Options :

A : Downloading the fine-tuned model for local deployment.

B : Directly using the model within the OCI Generative AI playground.

C : Creating a dedicated endpoint for the fine-tuned model.

D : Uploading the model to a separate Oracle Cloud service.

Answer: C

EXPERTY DESIGNED 1Z0-1127-25 PRACTICE TEST