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💻Interactive•30 min

Zero-shot vs Few-shot Prompting

Master zero-shot and few-shot prompting techniques.

Zero-shot vs Few-shot Prompting

Zero-shot Prompting

No examples provided. Model relies on:

  • Pre-training knowledge
  • Clear instructions

    • Example: "Classify this review as positive or negative: [review]"

    Few-shot Prompting

    Provide examples to guide the model.

    Example: "Classify reviews: Review: Great product! → Positive Review: Terrible quality → Negative Review: [new review] → "

    When to Use Which?

    Zero-shot:

  • Simple, well-defined tasks
  • Model already understands the task
  • Quick iteration

    • Few-shot:

  • Complex or ambiguous tasks
  • Specific output format needed
  • Consistent style required

    • Tips for Few-shot

  • Use 2-5 examples typically
  • Cover edge cases
  • Keep examples representative
  • Balance classes
  • Place examples before the query

    • 🎯 Key Takeaways

    • ✓Zero-shot relies on clear instructions only
    • ✓Few-shot provides examples to guide output
    • ✓More examples improve consistency
    • ✓Balance and diversity of examples matters

    📚 Additional Resources

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    Anatomy of Effective Prompts
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    Chain-of-Thought Reasoning