The Transformer Family
Read OriginalThis technical article provides a comprehensive summary of advancements in Transformer models, focusing on enhancements to the vanilla architecture for better long-term attention, reduced memory/computation costs, and adaptation for RL tasks. It includes detailed notation and explanations of core concepts like attention, self-attention, and multi-head mechanisms, serving as a resource for understanding modern NLP model evolution.
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