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Transformers are a powerful class of models in natural language processing and machine learning, revolutionizing various tasks. From attention mechanisms to self-attention, transformers have reshaped the landscape of deep learning.
Introduced by Vaswani et al., transformers use self-attention mechanisms to process input data in parallel, making them highly efficient for tasks like language translation, summarization, and various other sequence-based tasks.
A Comprehensive Survey on Applications of Transformers for Deep Learning Tasks: https://arxiv.org/abs/2306.07303
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