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Components of an Instruction-based Prompt
An instruction-based prompt is structured with key components to guide a large language model. It typically begins with a task description that outlines the objective, such as defining the task and the set of possible labels. It also uses indicators, like 'Input' and 'Polarity', to clearly demarcate the provided text and to signal where the output should be placed. The model is then expected to generate the correct label as a text completion that follows the output indicator.
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Ch.1 Pre-training - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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Example of a Complete Prompt for Polarity Classification
Components of an Instruction-based Prompt
Zero-Shot Learning with LLMs
Example of a Zero-Shot Prompt for Polarity Classification (Negative Sentiment)
Examples of Instruction-based Prompts for Polarity Classification
Using Descriptive Prompts for Novel Classification Tasks
Challenge of Prompting LLMs for Many-Category Classification
Example of a Zero-Shot Prompt for Polarity Classification (Positive Sentiment)
Example of a Zero-Shot Prompt for Polarity Classification (Positive Sentiment on Food)
Adapting Prompt Detail to an LLM's Task Familiarity
A developer needs a large language model to classify incoming customer support tickets. The goal is to sort each ticket into one of three specific categories: 'Technical Issue', 'Billing Inquiry', or 'General Feedback'. Which of the following prompts is best structured to achieve this task reliably and consistently?
Diagnosing Ineffective Prompt Instructions
Crafting an Instruction for a Novel Task
Instructing LLMs with Detailed Descriptions
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Example of a Complete Prompt for Polarity Classification
A user provides the following text to a large language model:
`Classify the sentiment of the following movie review. The sentiment can be one of {positive, negative}.
Review: "This film was a masterpiece of storytelling and cinematography." Sentiment:`
Which of the following options correctly breaks down the components of this prompt and their respective functions?
Analyzing a Flawed Prompt
Improving Prompt Structure for Better LLM Outputs