What is one of the primary reasons why transformer models are widely used in natural language processing tasks?

They utilize attention mechanisms, allowing them to capture global dependencies in the input sequence.

They have a shallow architecture, making them computationally efficient.

They rely solely on recurrent neural networks, enabling better long$-$term dependencies handling.

They are specifically designed for image processing tasks, offering superior performance compared to convolutional neural networks.