What You'll Build Embedding tables that give each token and each position a learned vector, a minimal forward pass that produces logits, and the loss function that measures how wrong the predictions are. Depends On Chapters 1-3, 5 (Value, Tokenizer, Helpers). Embeddings: Giving Tokens an Identity The model needs two pieces of information about each token: what the token is, and where it appe
Chapter 6: Embeddings, the Forward Pass, and the Loss Function
Gary Jackson·Dev.to··1 min read
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