Author: Kuladip Gawade

Introduction

Large Language Models (LLMs) have emerged as transformative tools capable of understanding and generating human language with unprecedented accuracy. These models, underpinned by the sophisticated transformer architecture, represent a significant leap forward in natural language processing. This article delves into the technical details that make LLMs so powerful, exploring the foundational components such as self-attention mechanisms, token embeddings, and the interplay of linear and softmax layers.