LLM Design Patterns

Table of Contents

1. Introduction to LLM Design Patterns
2. Data Cleaning for LLM Training
3. Data Augmentation
4. Handling Large Datasets for LLM Training
5. Data Versioning
6. Dataset Annotation and Labeling
7. Training Pipeline
8. Hyperparameter Tuning
9. Regularization
10. Checkpointing and Recovery
11. Fine-Tuning
12. Model Pruning
13. Quantization
14. Evaluation Metrics
15. Cross-Validation
16. Interpretability
17. Fairness and Bias Detection
18. Adversarial Robustness
19. Reinforcement Learning from Human Feedback
20. Chain-of-Thought Prompting
21. Tree-of-Thoughts Prompting
22. Reasoning and Acting
23. Reasoning WithOut Observation
24. Reflection Techniques
25. Automatic Multi-Step Reasoning and Tool Use
26. Retrieval-Augmented Generation
27. Graph-Based RAG
28. Advanced RAG
29. Evaluating RAG Systems
30. Agentic Patterns