prompt-engineering

Tips and tricks for working with Large Language Models like OpenAI's GPT-4.

Introduction

This guide provides insights into working with Large Language Models (LLMs) like OpenAI's GPT-4. It covers:

History of Language Models: A brief overview of the evolution of language models from pre-2000s to the present.
Understanding Prompts: Explanation of what prompts are, including hidden prompts, tokens, and token limits.
Prompt Engineering Strategies: Techniques for effective prompt engineering, including command grammars and semantic search.
Comparative Analysis: Differences between GPT-4 and GPT-3.5, highlighting improvements and capabilities.
Practical Applications: Real-world examples and strategies for embedding data, interpreting code, and fine-tuning models.

This document is a living resource, encouraging discussion and suggestions for improvements as the field evolves rapidly.