Example of a Sentiment Classification Task Instruction
An example of an instruction for a few-shot learning prompt is to direct the model to perform sentiment classification on text snippets, specifying the possible labels such as 'Positive', 'Negative', or 'Neutral'.
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Ch.2 Generative Models - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Ch.3 Prompting - Foundations of Large Language Models
Related
Example of a Few-Shot Prompt for Chinese-to-English Translation
Example of a Positive Sentiment Text Snippet for Classification
A user provides a language model with the text below. By analyzing the structure and the relationship between the inputs and outputs, determine the specific task the user is instructing the model to perform.
Review: This movie was a masterpiece. The acting was superb.Sentiment: PositiveReview: I was really disappointed with the plot.Sentiment: NegativeReview: The film was okay, but not memorable.Sentiment: NeutralDesigning a Prompt for Information Extraction
Predicting Model Output from a Pattern
Learn After
Example of a Negative Text Snippet for Sentiment Classification
Example of a Neutral Text Snippet for Sentiment Classification
Example of a Negative Input for Sentiment Classification (Hurtful Comment)
Example of a Positive Sentiment Text Snippet (Movie Review)
A developer wants to use a language model to sort customer feedback into categories based on the emotion expressed. Which of the following instructions is the clearest and most effective for this specific classification task?
Improving a Flawed Sentiment Classification Prompt
Crafting a Sentiment Classification Instruction