NVIDIA Generative AI LLMs - NCA-GENL Exam Practice Test
When using NVIDIA RAPIDS to accelerate data preprocessing for an LLM fine-tuning pipeline, which specific feature of RAPIDS cuDF enables faster data manipulation compared to traditional CPU-based Pandas?
Correct Answer: A
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Which technique is designed to train a deep learning model by adjusting the weights of the neural network based on the error between the predicted and actual outputs?
Correct Answer: A
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Which tool would you use to select training data with specific keywords?
Correct Answer: D
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What is the fundamental role of LangChain in an LLM workflow?
Correct Answer: A
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Which of the following contributes to the ability of RAPIDS to accelerate data processing? (Pick the 2 correct responses)
Correct Answer: B,D
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Why do we need positional encoding in transformer-based models?
Correct Answer: B
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In transformer-based LLMs, how does the use of multi-head attention improve model performance compared to single-head attention, particularly for complex NLP tasks?
Correct Answer: D
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You have developed a deep learning model for a recommendation system. You want to evaluate the performance of the model using A/B testing. What is the rationale for using A/B testing with deep learning model performance?
Correct Answer: A
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When preprocessing text data for an LLM fine-tuning task, why is it critical to apply subword tokenization (e.
g., Byte-Pair Encoding) instead of word-based tokenization for handling rare or out-of-vocabulary words?
g., Byte-Pair Encoding) instead of word-based tokenization for handling rare or out-of-vocabulary words?
Correct Answer: A
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Transformers are useful for language modeling because their architecture is uniquely suited for handling which of the following?
Correct Answer: A
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