LLM from Scratch Tutorial - Code and Train Qwen 3

Learn how to build a Large Language Model from the ground up in this comprehensive tutorial that walks you through creating Qwen 3 line by line. Master the fundamental concepts of transformer architecture while implementing key components including grouped query attention logic, RoPE positional embeddings, self-attention mechanisms, and feed-forward networks with SwiGLU activation. Explore advanced optimization techniques using the Muon optimizer and understand the intricacies of model configuration and training hyperparameters. Follow along with hands-on coding as you set up data loading and tokenization processes, implement the complete model architecture, and establish evaluation metrics. Experience the complete machine learning workflow from initial setup through the training loop execution, culminating in inference and text generation capabilities. Watch gradients flow and observe how neural networks learn in real-time while building one of the most advanced language models available today.