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Implement a decoder-only GPT model
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Write a small decoder-only transformer from scratch as four classes: multi-head self-attention with a causal mask, the feed-forward block, a decoder layer that combines them with residual connections and layer norm, and the GPT model that adds token and position embeddings, stacks the layers and projects to vocabulary logits.
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