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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