Techniques for effective prompt engineering
In the past two years, a wide array of prompt-engineering techniques have been developed. This section focuses on the essential ones, offering key strategies that you might find indispensable for daily interactions with ChatGPT and other LLM-based applications.
N-shot prompting
N-shot prompting is a term used in the context of training large language models, particularly for zero-shot or few-shot learning tasks. It is also called in-context learning and refers to the technique of providing the model with example prompts along with corresponding responses during training to steer the model’s behavior to provide more accurate responses.
The “N” in “N-shot” refers to the number of example prompts provided to the model. For instance, in a one-shot learning scenario, only one example prompt and its response are given to the model. In an N-shot learning scenario, multiple example prompts and responses...
