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Related Questions
- What are some common techniques used in prompt engineering to reduce the need for large amounts of training data?
- How can prompt engineering be used to transfer knowledge from one task to another?
- What are some strategies for designing prompts that elicit specific and relevant responses from large language models?
- Can you explain the concept of 'prompting' and how it relates to reducing the need for large amounts of training data?
- What role does contextualization play in prompt engineering, and how can it be used to reduce the need for training data?
- How can prompt engineering be used to adapt to new tasks or domains without requiring extensive retraining?
- What are some best practices for designing effective prompts that balance specificity and generality to reduce the need for large amounts of training data?
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