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Oracle Cloud Infrastructure Oracle Cloud Infrastructure 2025 Generative AI Professional

Oracle Cloud Infrastructure 2025 Generative AI Professional

Last Update Apr 2, 2025
Total Questions : 88

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Questions 2

Given the following code block:

history = StreamlitChatMessageHistory(key="chat_messages")

memory = ConversationBufferMemory(chat_memory=history)

Which statement is NOT true about StreamlitChatMessageHistory?

Options:

A.  

StreamlitChatMessageHistory will store messages in Streamlit session state at the specified key.

B.  

A given StreamlitChatMessageHistory will NOT be persisted.

C.  

A given StreamlitChatMessageHistory will not be shared across user sessions.

D.  

StreamlitChatMessageHistory can be used in any type of LLM application.

Discussion 0
Questions 3

What is the function of the Generator in a text generation system?

Options:

A.  

To collect user queries and convert them into database search terms

B.  

To rank the information based on its relevance to the user's query

C.  

To generate human-like text using the information retrieved and ranked, along with the user's original query

D.  

To store the generated responses for future use

Discussion 0
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Questions 4

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

Options:

A.  

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

B.  

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

C.  

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

D.  

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

Discussion 0
Questions 5

In which scenario is soft prompting appropriate compared to other training styles?

Options:

A.  

When there is a significant amount of labeled, task-specific data available

B.  

When the model needs to be adapted to perform well in a domain on which it was not originally trained

C.  

When there is a need to add learnable parameters to a Large Language Model (LLM) without task-specific training

D.  

When the model requires continued pretraining on unlabeled data

Discussion 0

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