AI Engineer: NLP and Large Language Models Flashcards
6 cards from real AI practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 AI Engineer: NLP and Large Language Models flashcards as text
What is the 'attention mechanism' in transformer-based models?
Answer: A mechanism that computes weighted relationships between all positions in a sequence
Attention computes a weighted sum of values based on query-key similarity, allowing the model to focus on relevant parts of the input regardless of distance.
What does 'tokenization' mean in the context of NLP preprocessing?
Answer: Splitting raw text into discrete units (tokens) for model input
Tokenization breaks raw text into tokens (words, subwords, or characters) that are then mapped to numeric IDs for model processing.
What is 'fine-tuning' a large language model (LLM)?
Answer: Continuing training of a pretrained LLM on task-specific data to adapt its behavior
Fine-tuning updates the pretrained model's weights on a smaller, task-specific dataset, adapting general language understanding to a specific domain or task.
What is 'prompt engineering' when working with LLMs?
Answer: Designing input text to guide LLM behavior without modifying model weights
Prompt engineering involves crafting input instructions, examples, and context to elicit desired outputs from an LLM without changing its parameters.
What is Retrieval-Augmented Generation (RAG)?
Answer: Combining an LLM with a retrieval system to ground responses in external documents
RAG retrieves relevant documents from an external knowledge base and injects them into the LLM's context, enabling up-to-date, grounded responses.
Which evaluation metric measures the overlap between generated text and human reference text using n-gram precision?
Answer: BLEU
BLEU (Bilingual Evaluation Understudy) measures n-gram precision between generated and reference text, commonly used for machine translation and text generation evaluation.