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Prompt Engineering Guide
😃 Basics
🟢 Introduction to AI
🟢 Prompting With ChatGPT
🟢 Prompt Engineering
🟢 Learn Prompting Embeds
🟢 Giving Instructions
🟢 Assigning Roles
🟢 Showing Examples
🟢 Formalizing Prompts
🟢 Chatbots
🟢 Combining Techniques
🟢 Priming Chatbots
🟢 OpenAI Playground
🟢 LLM Settings
🟢 Pitfalls of LLMs
🟢 Understanding AI Minds
🟢 The Learn Prompting Method
🟢 Starting Your Journey
💼 Applications
🟢 Introduction
🟢 Summarizing Text
🟢 Structuring Data
🟢 Contracts
🟢 Writing An Email
🟢 Different Writing Styles
🟢 Zapier for Emails
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🟢 Blogs
🧙‍♂️ Intermediate
🟢 Introduction
🟢 Chain-of-Thought Prompting
🟢 Zero-Shot Chain-of-Thought
🟦 Self-Consistency
🟦 Generated Knowledge
🟦 Least-to-Most Prompting
🟦 Dealing With Long Form Content
🟦 Revisiting Roles
🟢 What's in a Prompt?
🧪 Applied Prompting
🟢 Introduction
🟢 Multiple Choice Questions
🟢 Solve Discussion Questions
🟢 How to Build a Chatbot Using LLMs
🟢 Chatbot + Knowledge Base
🚀 Advanced Applications
🟢 Introduction
🟦 LLMs Using Tools
🟦 LLMs that Reason and Act
🟦 Code as Reasoning
🧠 Advanced
🟢 Introduction
Zero-Shot
🟢 Introduction
🟢 Emotion Prompting
🟢 Role Prompting
🟢 Re-reading (RE2)
🟢 Rephrase and Respond (RaR)
🟦 SimToM
◆ System 2 Attention (S2A)
Few-Shot
🟢 Introduction
🟢 Self-Ask
◆ K-Nearest Neighbor (KNN)
◆◆ Prompt Mining
Thought Generation
🟢 Introduction
🟦 Contrastive Chain-of-Thought
Ensembling
🟢 Introduction
Self-Criticism
🟢 Introduction
🟢 Self-Calibration
🟢 Chain-of-Verification (CoVe)
🟦 Self-Refine
🟦 Cumulative Reasoning
🟦 Reversing Chain-of-Thought (RCoT)
◆ Self-Verification
Decomposition
🟢 Introduction
🟦 Decomposed Prompting
🟦 Plan-and-Solve Prompting
🟦 Program-of-Thoughts
🟦 Tree of Thoughts
◆ Faithful Chain-of-Thought
◆ Recursion of Thought
◆ Skeleton-of-Thought
Special Topics
⚖️ Reliability
🟢 Introduction
🟢 Prompt Debiasing
🟦 Prompt Ensembling
🟦 LLM Self-Evaluation
🟦 Calibrating LLMs
🟦 Math
🖼️ Image Prompting
🟢 Introduction
🟢 Style Modifiers
🟢 Quality Boosters
🟢 Repetition
🟢 Weighted Terms
🟢 Fix Deformed Generations
🟢 Shot type
🟢 Midjourney
🟢 Resources
🔓 Prompt Hacking
🟢 Introduction
🟢 Prompt Injection
🟢 Prompt Leaking
🟢 Jailbreaking
🟢 Defensive Measures
🟢 Introduction
🟢 Filtering
🟢 Instruction Defense
🟢 Post-Prompting
🟢 Random Sequence Enclosure
🟢 Sandwich Defense
🟢 XML Tagging
🟢 Separate LLM Evaluation
🟢 Other Approaches
🟢 Offensive Measures
🟢 Introduction
🟢 Obfuscation/Token Smuggling
🟢 Payload Splitting
🟢 Defined Dictionary Attack
🟢 Virtualization
🟢 Indirect Injection
🟢 Recursive Injection
🟢 Code Injection
🔨 Tooling
🟢 Introduction
Prompt Engineering Tools
Prompt Engineering IDEs
🟢 Introduction
GPT-3 Playground
Dust
Soaked
Everyprompt
Prompt IDE
PromptTools
PromptSource
PromptChainer
Prompts.ai
Snorkel 🚧
Human Loop
Spellbook 🚧
Kolla Prompt 🚧
Lang Chain
OpenPrompt
OpenAI DALLE IDE
Dream Studio
Patience
Promptmetheus
PromptSandbox.io
The Forge AI
AnySolve
Conclusion
💪 Prompt Tuning
🟢 Introduction
Soft Prompts
Interpretable Soft Prompts
🎲 Miscellaneous
🟢 Detecting AI Generated Text
🟢 Introduction
🟢 Detection Trickery
🟢 Music Generation
Resources
📙 Vocabulary Reference
📚 Bibliography
📦 Prompted Products
🛸 Additional Resources
🔥 Hot Topics
✨ Credits
🧠 AdvancedEnsembling🟢 Introduction

🟢 Introduction to Ensembling Prompting

Last updated on September 4, 2024 by Valeriia Kuka

Welcome to the ensembling section of the advanced Prompt Engineering Guide.

Ensembling is based on using multiple prompts to tackle the problem and then aggregating these responses into a final output.

Stay tuned for ensembling techniques!

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