### Transformers have become the go-to model for many natural language processing tasks. They have been shown to outperform RNNs and LSTMs on many tasks. The transformer model was introduced in the paper [Attention is All You Need](https://arxiv.org/abs/1706.03762) by Vaswani et al. The transformer model is based on the self-attention mechanism, which allows the model to focus on different parts of the input sequence when making predictions. The transformer model consists of an encoder and a decoder, each of which is composed of multiple layers of self-attention and feed-forward neural networks. The transformer model has been shown to achieve state-of-the-art performance on many natural language processing tasks, including machine translation, text summarization, and question answering.
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