How LLMs Actually Work : Transformers, Tokens & Attention Explained

3-Second Blueprint (English)

1. Splits input prompts into word and subword tokens, mapping each into dense numerical embeddings encoding learned relationships.
2. Applies multi-layer self-attention so tokens dynamically weight relevant context across a sentence, resolving references.
3. Generates responses autoregressively by scoring vocabulary probabilities and appending one predicted token at a time.