Lean how to create an LLM from scratch. In this tutorial you will build Qwen 3, one line at a time. Watch gradients flow, models learn, and AI come alive in real-time.
Code on Google Colab - https://colab.research.google.com/drive/12ndGn_mI7R1GTbGS8I2EvajW50esJRRk?usp=sharing
GitHub - https://gist.github.com/vukrosic/94dc965a22b0892042f44fed25918598
⭐️ Contents ⭐️
⌨ (0:00:00) Intro & Demo
⌨ (0:01:46) Qwen 3 Architecture
⌨ (0:02:36) Prerequisites
⌨ (0:04:01) Code Setup & Imports
⌨ (0:05:26) Model Configuration
⌨ (0:08:26) Qwen 3 Specifics
⌨ (0:12:24) Training Hyperparameters
⌨ (0:17:18) Grouped Query Attention Logic
⌨ (0:18:56) Muon Optimizer Explained
⌨ (0:29:02) Data Loading & Tokenization
⌨ (0:32:37) RoPE Positional Embeddings
⌨ (0:36:56) Self-Attention Code
⌨ (0:44:28) Feed-Forward & SwiGLU
⌨ (0:47:36) Building the Final Model
⌨ (0:52:34) Evaluation & Optimizer Setup
⌨ (0:54:08) The Training Loop
⌨ (0:55:43) Running the Training
⌨ (0:58:38) Inference & Text Generation
⌨ (1:00:51) Final Results
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