The following are some guiding principles for crafting prompts to get relevant and accurate answers from a language model:
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Be specific: Clearly state what you are looking for in your prompt. The more specific your instructions, the better chance of getting the desired output. Avoid ambiguous or broad questions that could lead to unclear answers.
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Provide context: Give the language model relevant context about the topic or domain you're discussing. This can help set the right expectations and ensure the model understands the context of your question or request.
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Ask for reasoning or pros and cons: If you're seeking a reasoned response or a balanced perspective, explicitly ask the language model to provide pros and cons, advantages and disadvantages, or reasoning behind its answer. This can encourage more thoughtful and informative responses.
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Experiment and iterate: Prompt engineering often involves experimentation and iteration. Try different phrasings, rephrase your questions, or break down complex questions into simpler ones. Iterate on your prompts to find the ones that yield the most accurate and useful answers.
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Use system messages: System messages are instructions that help guide the behavior of the language model. You can use a system message at the beginning of the conversation to set the desired tone or role-play a specific scenario. These messages can help guide the model's responses.
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Verify information: While language models can provide useful information, it's essential to verify the accuracy and reliability of the answers they generate. Cross-check facts with trusted sources before relying on them.
Remember that prompt engineering is an iterative process, and it may take some experimentation and fine-tuning to achieve the desired results.