So far, we have turned raw token IDs into dense vectors that encode what a token is and where it sits in the sequence. That already feels like progress, but at this point the model still doesn’t understand anything. Each token only knows about itself. The real work happens next: the Transformer encoder. This is… Continue reading Building my own language model: Transformer encoder (Part 4)