Building a Transformer Language Model in PyTorch
Every component explained separately, now assembled into something you can train tonight.
PyTorch is an open-source deep learning framework developed by Facebookâs AI Research lab (FAIR). It is widely used for building and training neural networks with dynamic computation graphs, which allow for greater flexibility and debugging ease compared to static frameworks. PyTorch supports GPU acceleration, automatic differentiation through its autograd system, and seamless integration with Python and scientific libraries like NumPy. It is popular in both academic research and industry for tasks such as computer vision, natural language processing, and reinforcement learning, and it provides high-level APIs for building complex models efficiently using modules like torch.nn and torch.optim.
Every component explained separately, now assembled into something you can train tonight.
Almost nobody trains an image classifier from scratch. Here is what the alternative actually looks like.
Six lines in the right order, and the reasons each one has to be there.
Autograd is the computation graph you already built, constructed for you at runtime.