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Prompting techniques are strategies used to structure or phrase your input (or prompt) in such a way that it guides a language model, such as GPT, to provide more accurate, relevant, and useful responses. These techniques are essential because the way you ask or instruct the model determines the quality of the output.
Here are some common prompting techniques.
Zero-shot prompting is a technique used with LLMs where the model is asked to perform a task without any specific training or examples for that task. Instead, the model relies on its pre-existing knowledge and general language comprehension abilities to generate a response. By directly giving the model a task or question, zero-shot prompting leverages the patterns the model has learned during its general training to tackle new tasks. While this approach can yield accurate results, it may sometimes lead to challenges if the model lacks examples to clarify the expected output format...