Inside GPT-2: From Theory to Implementation

Step into the world of transformer-based language models with this in-depth 1:1 session on GPT-2. We’ll start by breaking down the theory behind GPT-2’s architecture — including tokenization, multi-head attention, and positional encoding — before moving into hands-on implementation.

You’ll learn how to:

• Understand the core mechanics of transformers and attention
• Build a mini GPT-2 from scratch using Python & PyTorch
• Explore how GPT-2 generates human-like text through learned patterns

Whether you’re a student, AI researcher, or developer, this session will give you a clear, intuitive understanding of how GPT-2 works — from mathematical foundations to working code.