Architectural Patterns for LLMs
The third chapter in this extensive guide gives a structured overview of on architectural patterns and how to leverage them for specific cases.
What is included:
Welcome to the third chapter of The Hitchhiker’s Guide to LLMs for Events.
In this release we delve into the key architectural patterns for working with LLMs – providing a structured approach to customization, optimization and deployment. Here’s what you’ll find:
- Fundamental concepts of prompt engineering
- Model customization through fine-tuning
- Pretraining from scratch and reinforcement learning from human feedback
- LLM agents and their growing strategic importance in AI applications
By the end of this chapter, readers will gain a comprehensive understanding of the various architectural patterns used in LLMs and how to leverage them effectively for specific use cases. Happy reading!
NOTE: This technical guide is designed for experts and professionals with some understanding of the relevant science.
