Lecture: Building Llama from Scratch
kalyan_kpl · x · 2026-07-13
This lecture, titled "Code Llama 4 from Scratch", explains how to implement the core components of an LLM from the ground up.
The comprehensive topics covered include:
- Basic LLM mechanics: next-word prediction, probability distribution, and sampling strategies
- Tokens and tokenization: BPE, vocabulary construction, encoding/decoding
- Word vectors and semantic representation: embedding, token relationships, context
- Core Transformer architecture: self-attention, Q/K/V, multi-head attention, masked attention
- Positional encoding and feed-forward networks: RoPE, FFN, linear layers, and activation functions
A tutorial link is included, making it a systematic implementation guide aimed at everyone from beginners to advanced users.
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