Transformer Decoder Architecture | Deep Learning | CampusX
The Decoder in a transformer architecture generates output sequences by attending to both the previous tokens (via masked self-attention) and the encoder’s output (via cross-attention). Each decoder layer consists of multi-head self-attention, cross-attention, and feed-forward layers. This structure allows the model to generate coherent sequences by considering both past outputs and relevant input context, making it effective for tasks like text generation and translation.
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⌚Time Stamps⌚
00:00 - Plan of Attack
02:22 - Simplified View
10:10 - Deep Dive into Architecture
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