![]() We will focus on the following in this tutorial: In today’s tutorial, we will cover the theory behind this neural network architecture called the Transformer. We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely. An excerpt from the paper best describes their proposal. proposed a simple yet effective change to the Neural Machine Translation models. In addition, to facilitate better learning, we also introduce the attention module. In our previous blog post, we covered Neural Machine Translation models based on Recurrent Neural Network architectures that include an encoder and a decoder. To learn how the attention mechanism evolved into the Transformer architecture, just keep reading.Ī Deep Dive into Transformers with TensorFlow and Keras: Part 1
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