Getting Started with Large Language Models: Key Things to Know
By Sebastian Raschka, Niels Bantilan
Free
Added 6 months ago
Description
An introductory guide to LLMs captures the evolving ecosystem and practical application.
Summary
This article presents an introductory guide to Large Language Models, discussing their architecture, applications, testing, optimization, and challenges in running them locally.
Key Insights
💡 LLMs' complexity and versatility can be mastered through the understanding and application of testing protocols, prompt engineering, and fine-tuning optimizations, significantly enhancing their usefulness across diverse applications. 💡 Advanced techniques such as in-context learning and efficient parameter fine-tuning are crucial for extending the capabilities of LLMs beyond their initial training conditions.