The field of natural language processing (NLP) has witnessed significant advancements in recent years, with the development of large language models (LLMs) being one of the most notable achievements. These models have demonstrated remarkable capabilities in understanding and generating human-like language, with applications ranging from language translation and text summarization to chatbots and content generation. In this article, we will provide a comprehensive guide on building a large language model from scratch, covering the fundamental concepts, architecture, and implementation details.
The goal of "building from scratch" typically involves implementing a . This is the architecture used by modern models like GPT-2, GPT-3, and Llama. 1. Data Preparation & Tokenization