Learn how to build and train your own Llama 3 model from scratch, step-by-step

This project enhances an existing Llama 3 language model implementation with optimized structure, detailed annotations, full dimension tracking, in-depth derivations, and bilingual documentation. It covers loading the model and tokenizer, converting text to embeddings, building Transformer blocks, implementing attention mechanisms, and predicting tokens. The goal is to provide a comprehensive understanding of Llama 3's architecture and reasoning process through explanations and step-by-step code implementations.