A developer has an effective prompt for generating Python code that sorts a list of numbers. To explore other ways to ask for the same outcome, they want to use a language model to generate alternative prompts. Which of the following instructions to the model is best suited for this specific goal?
0
1
Tags
Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models
Computing Sciences
Foundations of Large Language Models Course
Analysis in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
Related
A developer has an effective prompt for generating Python code that sorts a list of numbers. To explore other ways to ask for the same outcome, they want to use a language model to generate alternative prompts. Which of the following instructions to the model is best suited for this specific goal?
Constructing a Prompt for Expansion
A researcher has a prompt that successfully extracts key findings from scientific articles: "Identify the main conclusion from the following abstract." To improve their workflow, they want to use a language model to generate a diverse set of alternative prompts for this task. Which of the following instructions to the model would be most effective at generating prompts that vary significantly in their phrasing and approach?