Go to file
Ritvik19 3b28ce2d24 Added
- Skeleton-of-Thought: LLMs can do parallel decoding
- You Only Prompt Once: On the Capabilities of Prompt Learning on Large Language Models to Tackle Toxic Content
- LLMs as Database Administrators
- Outlines
2023-08-15 10:07:40 +05:30
.github Create FUNDING.yml 2023-02-01 18:22:13 -06:00
components add pages 2023-03-10 20:21:43 -06:00
guides Update prompts-applications.md 2023-04-03 15:58:14 -06:00
img new techniques 2023-06-08 14:52:35 -06:00
lecture add lecture slides 2023-02-19 07:51:04 -06:00
notebooks Replaced search tool with google-serper 2023-06-16 01:01:59 +01:00
pages Added 2023-08-15 10:07:40 +05:30
public add favicon 2023-03-13 21:13:09 -06:00
.gitignore remove folder 2023-04-13 02:21:31 -06:00
CITATION.cff Update CITATION.cff 2023-01-28 15:34:03 -06:00
LICENSE.md Create LICENSE.md 2022-12-17 14:12:10 -06:00
middleware.js multilanguage support 2023-03-30 18:43:20 -06:00
next-env.d.ts add site support 2023-03-10 17:22:18 -06:00
next.config.js fixed next.config.js 2023-06-04 20:45:08 +03:00
package-lock.json Update package-lock.json 2023-08-03 12:46:32 +09:00
package.json Update package.json 2023-08-03 12:45:10 +09:00
pnpm-lock.yaml change 2023-03-17 01:59:59 -06:00
README.md made changes 2023-06-06 19:06:11 -06:00
theme.config.tsx Added ru to theme.config.tsx 2023-06-04 20:12:33 +03:00
tsconfig.json add site support 2023-03-10 17:22:18 -06:00

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 for LLMs.

Happy Prompting!


Prompt Engineering for LLMs Course

Due to high demand, we've partnered with Maven to deliver a new cohort-based course on Prompt Engineering for LLMs.

Elvis Saravia, who has worked at companies like Meta AI and Elastic, and has years of experience in AI and LLMs, will be the instructor for this course.

This hands-on course will cover prompt engineering techniques/tools, use cases, exercises, and projects for effectively working and building with large language models (LLMs).

Our past learners range from software engineers to AI researchers and practitioners in organizations like LinkedIn, Amazon, JPMorgan Chase & Co., Intuit, Fidelity Investments, Coinbase, Guru, and many others.


Announcements / Updates

  • 🎓 New course on Prompt Engineering for LLMs announced! Enroll here!
  • 💼 We now offer several services like professional training, consulting, and talks.
  • 🌐 We now support 12 languages! Welcoming more translations.
  • 👩‍🎓 We crossed 800K learners in June 2023!
  • 🎉 We have launched a new web version of the guide here
  • 🔥 We reached #1 on Hacker News on 21 Feb 2023
  • 🎉 The Prompt Engineering Lecture went live here

Join our Discord

Follow us on Twitter

Subscribe to our Newsletter


Guides

You can also find the most up-to-date guides on our new website https://www.promptingguide.ai/.


Lecture

We have published a 1 hour lecture that provides a comprehensive overview of prompting techniques, applications, and tools.


Running the guide locally

To run the guide locally, for example to check the correct implementation of a new translation, you will need to:

  1. Install Node >=18.0.0
  2. Install pnpm if not present in your system. Check here for detailed instructions.
  3. Install the dependencies: pnpm i next react react-dom nextra nextra-theme-docs
  4. Boot the guide with pnpm dev
  5. Browse the guide at http://localhost:3000/

Appearances

Some places where we have been featured:


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}
}

License

MIT License

Feel free to open a PR if you think something is missing here. Always welcome feedback and suggestions. Just open an issue!