transformer layers
Transformer layers refer to a key component of transformer models, often used in natural language processing and sequence generation tasks. These layers consist of multiple sub-layers that employ self-attention mechanisms, allowing the model to weigh the importance of different words in a sentence, in order to better understand the context and meaning of the input sequence. Transformer layers are responsible for processing and transforming the input data through multiple stacked layers, enabling the model to capture complex dependencies and generate accurate predictions.
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