Welcome back to another edition of our weekly quiz series! As a professional interested in Large Language Models (LLMs) and prompt engineering, it's essential to stay sharp and up-to-date. Test your knowledge and identify the areas you may need to brush up on with these five new questions.
Dive into this week's questions and remember to check back next week for another set of stimulating quizzes!
Quiz:
In the context of LLMs, the term "fine-tuning" refers to: A. Adjusting the model's temperature B. Training the model on domain-specific data C. Modifying the structure of the model
Which of the following best describes a "zero-shot" prompt? A. A prompt without any examples B. A prompt with a single example C. A prompt with multiple examples
LLMs can be particularly helpful in addressing which of these business challenges? A. Email classification and filtering B. Image editing and manipulation C. Hardware troubleshooting
Match the prompt engineering term with its definition: A. Generative model | i. A model that takes an input and provides a classification or decision B. Discriminative model | ii. A model that can create new content based on the input provided
Which of the following techniques can be used to improve the clarity and relevance of LLM responses? A. Increasing model temperature B. Reformatting the input prompt C. Decreasing the number of tokens generated
How confident are you in your quiz performance? Regardless of the outcome, remember that learning is a continuous journey.
Join us next week for another round of quizzes to help you stay sharp in the world of prompt engineering!
Comments