PE Guide

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What is Prompt Engineering Guide ?

Prompt Engineering Guide is Github repo containing guides, papers, lecture, notebooks and resources for prompt engineering.

What is Prompt engineering ?

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.

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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.

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Guides

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

• Prompt Engineering - Introduction

• Prompt Engineering - LLM Settings

• Prompt Engineering - Basics of Prompting

• Prompt Engineering - Prompt Elements

• Prompt Engineering - General Tips for Designing Prompts

• Prompt Engineering - Examples of Prompts

• Prompt Engineering - Techniques

• Prompt Engineering - Zero-Shot Prompting

• Prompt Engineering - Few-Shot Prompting

• Prompt Engineering - Chain-of-Thought Prompting

• Prompt Engineering - Self-Consistency

• Prompt Engineering - Generate Knowledge Prompting

• Prompt Engineering - Tree of Thoughts (ToT)

• Prompt Engineering - Automatic Reasoning and Tool-use (ART)

• Prompt Engineering - Automatic Prompt Engineer

• Prompt Engineering - Active-Prompt

• Prompt Engineering - Directional Stimulus Prompting

• Prompt Engineering - ReAct Prompting

• Prompt Engineering - Multimodal CoT Prompting

• Prompt Engineering - Graph Prompting

• Prompt Engineering - Applications

• Prompt Engineering - Program-Aided Language Models

• Prompt Engineering - Generating Data

• Prompt Engineering - Generating Synthetic Dataset for RAG

• Prompt Engineering - Takling Generated Datasets Diversity

• Prompt Engineering - Generating Code

• Prompt Engineering - Graduate Job Classification Case Study

• Prompt Engineering - Models

• Prompt Engineering - Flan

• Prompt Engineering - ChatGPT

• Prompt Engineering - LLaMA

• Prompt Engineering - GPT-4

• Prompt Engineering - Model Collection

• Prompt Engineering - Risks and Misuses

• Prompt Engineering - Adversarial Prompting

• Prompt Engineering - Factuality

• Prompt Engineering - Biases

• Prompt Engineering - Papers

• Prompt Engineering - Overviews

• Prompt Engineering - Approaches

• Prompt Engineering - Applications

• Prompt Engineering - Collections

• Prompt Engineering - Tools

• Prompt Engineering - Notebooks

• Prompt Engineering - Datasets

• Prompt Engineering - Additional Readings

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Lecture

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

• Video Lecture

• Notebook with code

• Slides

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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/