Free Printable OCI Generative AI 2

Worksheets

OCI Generative AI 2 - 21 to 40

Total questions: 20

Worksheet time: 20mins

Name

Class

Date

What does a dedicated RDMA cluster network do during model fine-tuning and inference?

It limits the number of fine-tuned models deployable on the same GPU cluster.

It leads to higher latency in model inference.

It increases GPU memory requirements for model deployment.

It enables the deployment of multiple fine-tuned models within a single cluster

Which Oracle Accelerated Data Science (ADS) class can be used to deploy a Large Language Model (LLM) application to OCI Data Science model deployment?

Generative Ai

Text Loader

Chain Deployment

RetrievalQA

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

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

RAG Token retrieves documents only at the beginning of the response generation and uses those for the entire content.

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

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

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

Encoder-decoder

Generator

Ranker

Retriever

Which is NOT a typical use case for LangSmith Evaluators?

Evaluating factual accuracy of outputs

Assessing code readability

Detecting bias or toxicity

Measuring coherence of generated text.

What is the primary purpose of LangSmith Tracing?

To analyze the reasoning process of language models

To debug issues in language model outputs

To generate test cases for language models

To monitor the performance of language models.

You create a fine-tuning dedicated Al cluster to customize a foundational model with your custom training. How many unit hours are required for fine-tuning if the cluster is active for 10 hours?

30 unit hours

25 unit hours

20 unit hours

40 unit hours

How does the architecture of dedicated Al clusters contribute to minimizing GPU memory overhead for TFew fine-tuned model inference?

By optimizing GPU memory utilization for each model's unique parameters

By sharing base model weights across multiple fine-tuned models on the same group of GPUs

By loading the entire model into GPU memory for efficient processing

By allocating separate GPUs for each model instance.

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

LCELis an older Python library for building Large Language Models.

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

LCELis a programming language used to write documentation for LangChain.

LCELis a legacy method for creating chains in LangChain.

10.

Given a block of code: gaConversational Retrieval Chain. from_11m (11m, retriever=rety, memory=memory) when does a chain typically interact with memory during execution? After user input but before chain execution, and again after core logic but before output Only after the output has been generated Continuously throughout the entire chain execution process Before user input and after chain execution. Given the following code: prompt Prompt Template (input_variables= ["human_input", "city"], templatetemplate) Which statement is true about Prompt Template in relation to input_variables?

Prompt Template is unable to use any variables.

Prompt Template requires a minimum of two variables to function properly.

Prompt Template can support only a single variable at a time.

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

11.

Given a block of code: ga Conversational Retrieval Chain. from_11m (11m, retriever=rety, memory=memory) when does a chain typically interact with memory during execution?

After user input but before chain execution, and again after core logic but before output

Only after the output has been generated.

Continuously throughout the entire chain execution process

Before user input and after chain execution

12.

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

Conversation SummaryMemory

Conversation TokenBufferMemory

Conversation BufferMemory

Conversation ImageMemory

13.

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

Emphasis on syntactic clustering of word embeddings

Support for tokenizing longer sentences

Improved retrievals for Retrieval-Augmented Generation (RAG) systems

Capacity to translate text in over 20 languages.

14.

What is the primary function of the "temperature" parameter in the OCI Generative Al Generation models?

Controls the randomness of the model's output, affecting its creativity

Assigns a penalty to tokens that have already appeared in the preceding text

Determines the maximum number of tokens the model can generate per response

Specifies a string that tells the model to stop generating more content.

15.

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

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

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

"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.

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

16.

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

"Top p" selects tokens from the "Top k" tokens sorted by probability.

"Top p" assigns penalties to frequently occurring tokens.

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

"Top p" determines the maximum number of tokens per response.

17.

What does a higher number assigned to a token signify in the "Show Likelihoods" feature ofthe language model token generation?

The token is less likely to follow the current token.

The token will be the only one considered in the next generation step.

The token is unrelated to the current token and will not be used.

The token is more likely to follow the current token.

18.

What is the purpose of the "stop sequence" parameter in the OCI Generative Al Generation models?

It specifies a string that tells the model to stop generating more content.

It determines the maximum number of tokens the model can generate per response.

It controls the randomness of the model's output, affecting its creativity.

It assigns a penalty to frequently occurring tokens to reduce repetitive text.

19.

Why is normalization of vectors important before indexing in a hybrid search system?

It ensures that all vectors represent keywords only.

It significantly reduces the size of the database.

It converts all sparse vectors to dense vectors.

It standardizes vector lengths for meaningful comparison using metrics such as Cosine Similarity

20.

Which is a distinguishing feature of "Parameter-Efficient Fine-tuning (PEFT)" as opposed to classic "Fine-tuning in Large Language Model training?

PEFT involves only a few or new parameters and uses labeled, task-specific data.

PEFT modifies all parameters and is typically used when no training data exists.

PEFT does not modify any parameters but uses soft prompting with unlabeled data.

PEFT modifies all parameters and uses unlabeled, task-agnostic data.

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OCI Generative AI 2 - 21 to 40

Total questions: 20

Worksheet time: 20mins

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