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Awesome-Prompt-Engineering
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
https://github.com/promptslab/Awesome-Prompt-Engineering
Last synced: 3 days ago
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Papers
- Text Mining for Prompt Engineering: Text-Augmented Open Knowledge Graph Completion via PLMs
- A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT
- Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery
- Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Models
- Progressive Prompts: Continual Learning for Language Models
- Batch Prompting: Efficient Inference with LLM APIs
- Successive Prompting for Decompleting Complex Questions
- Structured Prompting: Scaling In-Context Learning to 1,000 Examples
- Large Language Models Are Human-Level Prompt Engineers
- Ask Me Anything: A simple strategy for prompting language models
- Prompting GPT-3 To Be Reliable
- Decomposed Prompting: A Modular Approach for Solving Complex Tasks
- PromptChainer: Chaining Large Language Model Prompts through Visual Programming
- Investigating Prompt Engineering in Diffusion Models
- Show Your Work: Scratchpads for Intermediate Computation with Language Models
- Multimodal Chain-of-Thought Reasoning in Language Models
- On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning
- Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought
- On the Advance of Making Language Models Better Reasoners
- Large Language Models are Zero-Shot Reasoners
- Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering
- Chain of Thought Prompting Elicits Reasoning in Large Language Models
- Generated Knowledge Prompting for Commonsense Reasoning
- Large Language Models Can Be Easily Distracted by Irrelevant Context
- Calibrate Before Use: Improving Few-Shot Performance of Language Models
- Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves
- Prompting for Multimodal Hateful Meme Classification
- PLACES: Prompting Language Models for Social Conversation Synthesis
- Show Your Work: Scratchpads for Intermediate Computation with Language Models
- Reframing Instructional Prompts to GPTk's Language
- Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity
- The Power of Scale for Parameter-Efficient Prompt Tuning
- Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm
- Prefix-Tuning: Optimizing Continuous Prompts for Generation
- Multimodal Chain-of-Thought Reasoning in Language Models
- On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning
- ReAct: Synergizing Reasoning and Acting in Language Models
- Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought
- On the Advance of Making Language Models Better Reasoners
- Large Language Models are Zero-Shot Reasoners
- Reasoning Like Program Executors
- Self-Consistency Improves Chain of Thought Reasoning in Language Models
- Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?
- Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering
- Chain of Thought Prompting Elicits Reasoning in Large Language Models
- Generated Knowledge Prompting for Commonsense Reasoning
- BERTese: Learning to Speak to BERT
- Large Language Models Can Be Easily Distracted by Irrelevant Context
- Crawling the Internal Knowledge-Base of Language Models
- Discovering Language Model Behaviors with Model-Written Evaluations
- Calibrate Before Use: Improving Few-Shot Performance of Language Models
- Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves
- PLACES: Prompting Language Models for Social Conversation Synthesis
- Commonsense-Aware Prompting for Controllable Empathetic Dialogue Generation
- PAL: Program-aided Language Models
- Legal Prompt Engineering for Multilingual Legal Judgement Prediction
- Conversing with Copilot: Exploring Prompt Engineering for Solving CS1 Problems Using Natural Language
- AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts
- Constitutional AI: Harmlessness from AI Feedback
- Ignore Previous Prompt: Attack Techniques For Language Models
- Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods
- Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
- How Can We Know What Language Models Know?
- Promptagator: Few-shot Dense Retrieval From 8 Examples
- The Unreliability of Explanations in Few-shot Prompting for Textual Reasoning
- Making Pre-trained Language Models Better Few-shot Learners
- Language Models are Few-Shot Learners
- A Taxonomy of Prompt Modifiers for Text-To-Image Generation
- Design Guidelines for Prompt Engineering Text-to-Image Generative Models
- High-Resolution Image Synthesis with Latent Diffusion Models
- ERNIE-Music: Text-to-Waveform Music Generation with Diffusion Models
- Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models
- Dreamix: Video Diffusion Models are General Video Editors
- Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation
- Piloting Copilot and Codex: Hot Temperature, Cold Prompts, or Black Magic?
- Commonsense-Aware Prompting for Controllable Empathetic Dialogue Generation
- PAL: Program-aided Language Models
- Conversing with Copilot: Exploring Prompt Engineering for Solving CS1 Problems Using Natural Language
- Plot Writing From Scratch Pre-Trained Language Models
- Ignore Previous Prompt: Attack Techniques For Language Models
- Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods
- Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
- Toxicity Detection with Generative Prompt-based Inference
- How Can We Know What Language Models Know?
- Promptagator: Few-shot Dense Retrieval From 8 Examples
- The Unreliability of Explanations in Few-shot Prompting for Textual Reasoning
- Making Pre-trained Language Models Better Few-shot Learners
- Language Models are Few-Shot Learners
- A Taxonomy of Prompt Modifiers for Text-To-Image Generation
- ERNIE-Music: Text-to-Waveform Music Generation with Diffusion Models
- Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models
- Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation
- Noise2Music: Text-conditioned Music Generation with Diffusion Models
- Dreamix: Video Diffusion Models are General Video Editors
- DALL·E: Creating Images from Text
- ERNIE-Music: Text-to-Waveform Music Generation with Diffusion Models
- AudioLM: a Language Modeling Approach to Audio Generation
- Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models
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AI Content Detectors
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Models
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Courses
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Tutorials
- Prompt Engineering Guide by SudalaiRajkumar
- Best practices for prompt engineering with OpenAI API
- Prompt Engineering Guide: How to Engineer the Perfect Prompts
- How to write good prompts
- A Generic Framework for ChatGPT Prompt Engineering
- Methods of prompt programming
- Prompt Engineering 101 - Introduction and resources
- Prompt Engineering 101
- A beginner-friendly guide to generative language models - LaMBDA guide
- A Complete Introduction to Prompt Engineering for Large Language Models
- Prompt Engineering Guide: How to Engineer the Perfect Prompts
- 3 Principles for prompt engineering with GPT-3
- Awesome ChatGPT Prompts
- OpenAI Cookbook
- Prompt Engineering by Microsoft
- How to write good prompts
- Generative AI with Cohere: Part 1 - Model Prompting
- DALLE Prompt Book
- Prompt Engineering Guide: How to Engineer the Perfect Prompts
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Communities
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Videos
- ChatGPT Guide: 10x Your Results with Better Prompts
- Language Models and Prompt Engineering: Systematic Survey of Prompting Methods in NLP
- Prompt Engineering 101: Autocomplete, Zero-shot, One-shot, and Few-shot prompting
- Advanced ChatGPT Prompt Engineering
- ChatGPT: 5 Prompt Engineering Secrets For Beginners
- CMU Advanced NLP 2022: Prompting
- Prompt Engineering - A new profession ?
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Tools & Code
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Apis
- [HuggingFace - Source |
- [Anthropic
- [HuggingFace - Source |
- [OpenAI
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Datasets
Programming Languages
Categories
Sub Categories
Keywords
gpt-3
7
chatgpt
6
llm
5
transformers
5
machine-learning
5
ai
4
large-language-models
4
prompt-engineering
4
language-model
3
python
3
rag
3
prompts
3
human-feedback
3
reinforcement-learning
3
deep-learning
3
prompt-toolkit
3
nlp
3
chatgpt-api
2
developer-tools
2
gpt-3-prompts
2
vector-database
2
llmops
2
generative-ai
2
pytorch
2
question-answering
2
natural-language-processing
2
artificial-intelligence
2
application
2
gpt
2
gpt-2
2
openai
2
semantic-search
1
natural-language-understanding
1
nlp-library
1
information-retrieval
1
squad
1
bert
1
summarization
1
nlp-machine-learning
1
debugging
1
chatgpt-python
1
gpt-4
1
gpt-4-api
1
gpt3-library
1
prompt-tuning
1
prompt-versioning
1
prompting
1
promptversioning
1
ai-monitoring
1
ai-observability
1