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Transformer architectures have fundamentally changed how we approach sequence modeling. The self-attention mechanism allows the model to weigh the importance of different parts of the input...
Key insight: The attention mechanism can be viewed as a soft lookup table, where queries, keys, and values interact to produce context-aware representations.
Connected to: Neural Network Basics, Attention Mechanisms, GPT Architecture
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