In this tutorial, we explore how to build neural networks from scratch using Tinygrad while remaining fully hands-on with tensors, autograd, attention mechanisms, and transformer architectures. We progressively build every component ourselves, from basic tensor operations to multi-head attention, transformer blocks, and, finally, a working mini-GPT model. Through each stage, we observe how Tinygrad’s simplicity
The post How to Implement Functional Components of Transformer and Mini-GPT Model from Scratch Using Tinygrad to Understand Deep Learning Internals appeared first on MarkTechPost. Read More
