NCA-GENL Practice Questions - NVIDIA-Certified Associate Generative AI LLMs Exam - NCA-GENL Practice Questions - NVIDIA-Certified Associate Generative AI LLMs Exam

Question 1

What is the primary role of a transformer's self-attention mechanism in a large language model?

It allows each token in a sequence to attend to all other tokens, capturing long-range dependencies regardless of their distance It filters out irrelevant words before they enter the model using a convolutional layer It converts input tokens into dense vectors of fixed size for downstream processing It compresses the input sequence into a single context vector for the decoder

Correct Answer:

It allows each token in a sequence to attend to all other tokens, capturing long-range dependencies regardless of their distance

Question 2

In the context of large language models, what is 'tokenization' and why does it matter?

The process of splitting raw text into sub-word or word-level units that the model processes; it determines vocabulary size and how the model handles rare words The process of assigning unique integer IDs to full sentences before feeding them to the model A security step that strips personally identifiable information from training data The process of converting model outputs from logits to human-readable text

Correct Answer:

The process of splitting raw text into sub-word or word-level units that the model processes; it determines vocabulary size and how the model handles rare words

Question 3

What is Retrieval-Augmented Generation (RAG) and what problem does it solve?

RAG combines a retrieval system (vector database) with an LLM so the model can answer questions using up-to-date or private knowledge not in its training data RAG is a technique for reducing hallucinations by averaging outputs from multiple LLMs RAG is a fine-tuning method that adds a retrieval head to the transformer so it learns to cite sources RAG generates embeddings for documents and stores them in the model's context window for fast lookup

Correct Answer:

RAG combines a retrieval system (vector database) with an LLM so the model can answer questions using up-to-date or private knowledge not in its training data

Question 4

What are embeddings in the context of LLMs and how are they used in RAG pipelines?

Dense vector representations of text that capture semantic meaning; similar texts have high cosine similarity, enabling nearest-neighbor search for retrieval Compressed model weights stored in floating-point 16-bit format to reduce GPU memory usage Integer lookup tables mapping tokens to their positions in the vocabulary Sparse TF-IDF vectors used to score document relevance using keyword frequency

Correct Answer:

Dense vector representations of text that capture semantic meaning; similar texts have high cosine similarity, enabling nearest-neighbor search for retrieval

Question 5

What is the difference between zero-shot and few-shot prompting?

Zero-shot asks the model to perform a task with no examples; few-shot provides a small number of input-output examples in the prompt to guide the model Zero-shot uses no system prompt; few-shot uses a system prompt with detailed instructions Zero-shot generates one output; few-shot generates multiple outputs for comparison Zero-shot is used during training; few-shot is used during inference

Correct Answer:

Zero-shot asks the model to perform a task with no examples; few-shot provides a small number of input-output examples in the prompt to guide the model

Question 1

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Prepare with the NCA-GENL Practice Questions - NVIDIA-Certified Associate Generative AI LLMs Exam practice quiz. This question bank includes 100 questions covering context, model, application, primary, and role. Use it to review important concepts, identify knowledge gaps, and build confidence for the related exam, course, or assessment.

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NCA-GENL Practice Questions - NVIDIA-Certified Associate Generative AI LLMs Exam

This practice set contains 100 questions from the matching question bank and focuses on context, model, application, primary, and role. Work through each question carefully, review the provided solutions, and revisit topics that need more study before your next attempt.

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NCA-GENL Practice Questions - NVIDIA-Certified Associate Generative AI LLMs Exam

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