Prompt Engineering Guide by FlowGPT
  • Group 1
    • Introduction
    • Introduction to Prompt Engineering
      • Introduction to Prompt Engineering
      • The Role of Prompt Engineering in NLP Tasks
  • Group 2
    • Basics of Prompt Engineering
      • Understanding the Prompt Format
      • Prompt Tokens and Special Tokens
      • Task Formulation and Specifications
      • Identifying the Desired Output
      • Writing Clear and Unambiguous Prompts
  • Multiple Techniques in Prompt Engineering
    • Rule-based Techniques
    • Supervised Techniques
    • Pre-Training and Transfer Learning
    • Transfer Learning
    • Reinforcement Learning Techniques
    • Policy Gradient Methods
  • Group 3
    • Advanced Applications of Prompt Engineering
      • Question Answering Systems
      • Prompting Techniques for Factoid QA
      • Text Generation and Summarization
      • Dialogue Systems
      • Contextual Prompts for Conversational Agents
  • Group 4
    • Prominent Prompt Engineering Models
      • GPT3 vs GPT4
      • T5 and BART Models
      • RoBERTa, ALBERT, and ELECTRA
      • Transformer-XL and XLNet
  • Group 5
    • Examples and Code Generation
      • Code Generation and Assistance
      • Content creation and writing assistance
      • Language Translation and Interpretation
  • Group 6
    • Research Papers and Publications
      • Seminal Papers on Prompt Engineering
      • Recent Advances and Findings
      • Prominent Researchers and Labs
  • Group 7
    • Tools and Frameworks for Prompt Engineering
      • OpenAI API and Libraries
      • Hugging Face Transformers
      • Other NLP Frameworks and Libraries
  • Group 8
    • Advanced Topics in Prompt Engineering
      • Few-shot and Zero-shot Learning
      • Meta-learning and meta-prompts
      • Active learning and prompt adaptation
      • Generating knowledge prompts
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  1. Group 2

Basics of Prompt Engineering

Understanding the Prompt FormatPrompt Tokens and Special TokensTask Formulation and SpecificationsIdentifying the Desired OutputWriting Clear and Unambiguous Prompts
PreviousThe Role of Prompt Engineering in NLP TasksNextUnderstanding the Prompt Format

Last updated 2 years ago