Few-Shot Sentiment Classification with LLMs

Background

This prompt tests an LLM's text classification capabilities by prompting it to classify a piece of text into the proper sentiment using few-shot examples.

Prompt

prompt.txt

This is awesome! // Negative
This is bad! // Positive
Wow that movie was rad! // Positive
What a horrible show! //

Code / API

file.py

from openai import OpenAI
client = OpenAI()
 
response = client.chat.completions.create(
    model="gpt-4",
    messages=[
        {
        "role": "user",
        "content": "This is awesome! // Negative\nThis is bad! // Positive\nWow that movie was rad! // Positive\nWhat a horrible show! //"
        }
    ],
    temperature=1,
    max_tokens=256,
    top_p=1,
    frequency_penalty=0,
    presence_penalty=0
)

Reference

Prompt Engineering Guide (opens in a new tab) (16 March 2023)

Sentimate Classification Coding