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README.md
Prompt Engineering Guide
Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Prompt engineering skills help to better understand the capabilities and limitations of large language models (LLMs). Researchers use prompt engineering to improve the capacity of LLMs on a wide range of common and complex tasks such as question answering and arithmetic reasoning. Developers use prompt engineering to design robust and effective prompting techniques that interface with LLMs and other tools.
Motivated by the high interest in developing with LLMs, we have created this new prompt engineering guide that contains all the latest papers, learning guides, lectures, references, and tools related to prompt engineering.
Happy Prompting!
Table of Contents
Guides
The following are a set of guides on prompt engineering developed by us. Guides are work in progress.
- Prompt Engineering - Introduction
- Prompt Engineering - Basic Prompting
- Prompt Engineering - Advanced Prompting
- Prompt Engineering - Adversarial Prompting
- Prompt Engineering - Miscellaneous Topics
Tools & Libraries
(Sorted by Name)
- AI Test Kitchen
- betterprompt
- DreamStudio
- DUST
- Dyno
- EveryPrompt
- GPT Index
- GPTTools
- hwchase17/adversarial-prompts
- Interactive Composition Explorer
- LangChain
- LearnGPT
- Lexica
- loom
- Metaprompt
- OpenAI Playground
- OpenPrompt
- Playground
- Prodia
- Prompt Base
- Prompt Engine
- Prompt Generator for OpenAI’s DALL-E 2
- Promptable
- PromptInject
- Prompts.ai
- Promptly
- PromptSource
- Promptist
- Scale SpellBook
- sharegpt
- ThoughtSource
- Visual Prompt Builder
Blog, Guides, Tutorials and Other Readings
(Sorted by Name)
- 3 Principles for prompt engineering with GPT-3
- A beginner-friendly guide to generative language models - LaMBDA guide
- A Complete Introduction to Prompt Engineering for Large Language Models
- A Generic Framework for ChatGPT Prompt Engineering
- AI Content Generation
- AI’s rise generates new job title: Prompt engineer
- Awesome ChatGPT Prompts
- Best 100+ Stable Diffusion Prompts
- Best practices for prompt engineering with OpenAI API
- Building GPT-3 applications — beyond the prompt
- ChatGPT, AI and GPT-3 Apps and use cases
- CMU Advanced NLP 2022: Prompting
- Curtis64’s set of prompt gists
- DALL·E 2 Prompt Engineering Guide
- DALL·E 2 Preview - Risks and Limitations
- DALLE Prompt Book
- DALL-E, Make Me Another Picasso, Please
- Diffusion Models: A Practical Guide
- Exploiting GPT-3 Prompts
- Exploring Prompt Injection Attacks
- Extrapolating to Unnatural Language Processing with GPT-3’s In-context Learning: The Good, the Bad, and the Mysterious
- Generative AI with Cohere: Part 1 - Model Prompting
- Giving GPT-3 a Turing Test
- GPT-3 & Beyond
- GPT3 and Prompts: A quick primer
- How to Draw Anything
- How to get images that don’t suck
- How to make LLMs say true things
- How to write good prompts
- Introduction to Reinforcement Learning with Human Feedback
- In defense of prompt engineering
- Language Models and Prompt Engineering: Systematic Survey of Prompting Methods in NLP
- Learn Prompting
- Methods of prompt programming
- Mysteries of mode collapse
- NLP for Text-to-Image Generators: Prompt Analysis
- NLP with Deep Learning CS224N/Ling284 - Lecture 11: Promting, Instruction Tuning, and RLHF
- Notes for Prompt Engineering by sw-yx
- OpenAI Cookbook
- OpenAI Prompt Examples for several applications
- Pretrain, Prompt, Predict - A New Paradigm for NLP
- Prompt Engineering 101 - Introduction and resources
- Prompt Engineering 101: Autocomplete, Zero-shot, One-shot, and Few-shot prompting
- Prompt Engineering 101
- Prompt Engineering - A new profession ?
- Prompt Engineering by co:here
- Prompt Engineering by Microsoft
- Prompt Engineering: The Career of Future
- Prompt engineering davinci-003 on our own docs for automated support (Part I)
- Prompt Engineering Guide: How to Engineer the Perfect Prompts
- Prompt Engineering in GPT-3
- Prompt Engineering Template
- Prompt Engineering Topic by GitHub
- Prompt Engineering: From Words to Art
- Prompt Engineering with OpenAI’s GPT-3 and other LLMs
- Prompt injection attacks against GPT-3
- Prompt injection to read out the secret OpenAI API key
- Prompting in NLP: Prompt-based zero-shot learning
- Prompting Methods with Language Models and Their Applications to Weak Supervision
- Prompts as Programming by Gwern
- Reverse Prompt Engineering for Fun and (no) Profit
- So you want to be a prompt engineer: Critical careers of the future
- Simulators
- Start with an Instruction
- Talking to machines: prompt engineering & injection
- The Book - Fed Honeypot
- The ChatGPT Prompt Book
- The Mirror of Language
- Unleash Your Creativity with Generative AI: Learn How to Build Innovative Products!
- Using GPT-Eliezer against ChatGPT Jailbreaking
- What Is ChatGPT Doing … and Why Does It Work?
If you are using the guide for your work, please cite us as follows:
@article{Saravia_Prompt_Engineering_Guide_2022,
author = {Saravia, Elvis},
journal = {https://github.com/dair-ai/Prompt-Engineering-Guide},
month = {12},
title = {{Prompt Engineering Guide}},
year = {2022}
}
Feel free to open a PR if you think something is missing here. Always welcome feedback and suggestions. Just open an issue!