Learn how to build and train a Generative Pretrained Transformer (GPT) model from scratch using Python and PyTorch. Understand the internal mechanisms of GPT models, including self-attention and multi-head attention. Follow step-by-step instructions to construct the GPT architecture, tokenize data, implement self-attention, and train the model on a dataset. Discover techniques to improve model performance and optimize training and inference processes.
Table of contents
Build And Train GPT From ScratchLet’s start building the GPT Language ModelSelf-attention: The basic building block of the TransformerLet’s put everything together in a single nn.ModulePutting it all together in a Transformer BlockGPT Model ArchitectureLet’s Train Our GPT Transformer ModelSort: