Please polish the following "Please polish “The Transformer is an influential deep learning model introduced in the paper "Attention is All You Need" by NAME_1 et al. in 2017. It has since become the foundation of many natural language processing (NLP) tasks, including machine translation, language modeling, text generation, question answering, and more. The Transformer's success can be attributed to its novel self-attention mechanism, which allows it to efficiently capture long-range dependencies and relationships between different parts of the input sequence. Traditional recurrent neural networks (RNNs) and long short-term memory (LSTM) networks, which were previously dominant in NLP, often struggled with long sequences due to the sequential nature of their computations. The Transformer, in contrast, allows for parallel computation across the entire input sequence, enabling it to process long sequences more effectively. This parallelism is made possible by the attention mechanism, which computes similarity scores between all pairs of input tokens, allowing the model to focus on the most relevant information at each step. The self-attention mechanism is part of the broader attention mechanism family, which includes variants such as encoder-decoder attention and multi-head attention.The Transformer architecture consists of an encoder and a decoder, each composed of multiple layers. The encoder is responsible for processing the input sequence, while the decoder generates the output sequence. "