This repository contains a collection of Jupyter Notebooks demonstrating various prompting techniques used in natural language processing (NLP) and machine learning. Each notebook provides an introduction, implementation details, and examples of how to apply the technique effectively.

1. Active Prompting
2. Automatic Chain-of-Thought Prompting
3. Automatic Prompt Engineer (APE)
4. Chain-of-Thought Prompting
5. Directional Stimulus Prompting
6. Few-shot Prompting
7. Generated Knowledge Prompting
8. Multimodal Chain-of-Thought Prompting
9. Program-aid Prompting
10. ReAct Prompting
11. Self-consistency Prompting
12. Synthetic Prompting
13. Tree-of-Thought Prompting
14. Zero-Shot Prompting
15. Zero-Shot Chain-of-Thought Prompting
16. Reflexion Prompting

1. RAG with local models