Answer / Ramesh Thakur

Transformers are a type of neural network architecture used in natural language processing tasks. They consist of self-attention mechanisms that allow the model to focus on relevant parts of input sequences, and multi-head attention mechanisms that enable the model to process information from multiple aspects simultaneously. Transformers can be stacked into encoder-decoder architectures for sequence-to-sequence tasks like machine translation or summarization. Their self-attention layers learn to weight the importance of different words in a sentence, making them particularly effective for handling long sequences.

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