Prompt engineering and priming GPT

Let us pause and provide some context before returning to discuss the next part of the code.

Prompt engineering is a technique used in NLP to design effective prompts or instructions when interacting with LLMs. It involves carefully crafting the input given to a model to elicit the desired output. By providing specific cues, context, or constraints in the prompts, prompt engineering aims to guide the model’s behavior and encourage the generation of more accurate, relevant, or targeted responses. The process often involves iterative refinement, experimentation, and understanding the model’s strengths and limitations to optimize the prompt for improved performance in various tasks, such as question-answering summarization or conversation generation. Effective prompt engineering plays a vital role in harnessing the capabilities of LMs and shaping their output to meet specific user requirements.

Let’s review one of the most...