This article introduces a practical guide to building GPT using 60 lines of code, providing a convenient way for developers to explore the foundation of the large model era. As a generative pre-training Transformer, GPT is increasingly used in fields such as text generation, email writing, book summarization, and code writing. The guide details the steps to build a GPT model, including key operations such as token integer representation, text decomposition, and predicted probability. It aims to lower the entry barrier for developers and enable more people to experience and apply GPT technology. Please refer to the original link for details.
Recently, a practical guide guides developers on how to build GPT using 60 lines of code, exploring the foundation of the large model era. As a generative pre-training Transformer neural network structure, GPT has become the core of AI and is widely used. By reducing the number of training parameters, GPT can be used for text generation and many other applications, including writing emails, summarizing books, writing code, etc. The steps to build a GPT model include operations such as token integer representation, text decomposition, and predicted probability. Please refer to the original link for details.The release of this guide will help promote the popularization and application of GPT technology, provide developers with more convenient ways to learn and practice, and thereby promote innovative development in the field of artificial intelligence. By simplifying the construction process of GPT, the technical threshold is lowered and more people have the opportunity to participate in the research and application of AI technology.