Explain the concept of attention mechanisms in NLP models and provide examples of their application in tasks such as machine translation or text summarization.

Attention mechanisms in NLP models allow the model to focus on relevant parts of the input sequence when making predictions. Rather than processing the entire input sequence at once, attention mechanisms enable the model to selectively attend to specific parts of the input sequence that are most relevant to the current output.