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chinar on Instagram: "Hi Folks! For day 12 of Building a LLM from scratch I understand what is causal self- attention. Causal self-attention ensures an LLM never looks into the future. By masking attention weights above the diagonal, each token can attend only to itself and past tokens, making next-word prediction truly autoregressive. Instead of masking after softmax (which breaks probability normalization), we efficiently mask attention scores with -∞ before softmax. We also apply dropout on a
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