llama3-from-scratch
Discover a comprehensive guide to implementing Llama3 from scratch using direct tensor and matrix operations. This article explains how to load model weights provided by Meta, use tiktoken for tokenization, and delve into embedding normalization and self-attention mechanics. Gain insights into configuring the transformer model that features 32 layers and multi-head attention, facilitating an understanding of neural network dynamics without heavy reliance on built-in neural modules.
