EMT Practice Test

1. Question Content...

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Question1: Which feature of the HuggingFace Transformers library makes it particularly suitable for fine-tuning large language models on NVIDIA GPUs?

Question2: In the context of fine-tuning LLMs, which of the following metrics is most commonly used to assess the performance of a fine-tuned model?

Question3: Which aspect in the development of ethical AI systems ensures they align with societal values and norms?

Question4: What type of model would you use in emotion classification tasks?

Question5: In the context of developing an AI application using NVIDIA's NGC containers, how does the use of containerized environments enhance the reproducibility of LLM training and deployment workflows?

Question6: What is 'chunking' in Retrieval-Augmented Generation (RAG)?

Question7: Which tool would you use to select training data with specific keywords?

Question8: In the context of data preprocessing for Large Language Models (LLMs), what does tokenization refer to?

Question9: Which technology will allow you to deploy an LLM for production application?

Question10: What is the primary purpose of applying various image transformation techniques (e.g., flipping, rotation, zooming) to a dataset?

Question11: Transformers are useful for language modeling because their architecture is uniquely suited for handling which of the following?

Question12: Which of the following is a key characteristic of Rapid Application Development (RAD)?

Question13: Why do we need positional encoding in transformer-based models?

Question14: In neural networks, the vanishing gradient problem refers to what problem or issue?

Question15: What are the main advantages of instructed large language models over traditional, small language models (<
300M parameters)? (Pick the 2 correct responses)

Question16: Which technique is used in prompt engineering to guide LLMs in generating more accurate and contextually appropriate responses?

Question17: Which Python library is specifically designed for working with large language models (LLMs)?

Question18: When comparing and contrasting the ReLU and sigmoid activation functions, which statement is true?

Question19: In the context of transformer-based large language models, how does the use of layer normalization mitigate the challenges associated with training deep neural networks?

Question20: Which metric is commonly used to evaluate machine-translation models?

Question21: Which calculation is most commonly used to measure the semantic closeness of two text passages?

Question22: 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?

Question23: Which principle of Trustworthy AI primarily concerns the ethical implications of AI's impact on society and includes considerations for both potential misuse and unintended consequences?