For this activity follow Neural machine translation with a Transformer and Keras.
Submit completed Colab notebook showing generated output.
The dataset used for training the model is the Multi30k dataset. This dataset contains about 30,000 sentences written in both English and German.
A Transformer model is a type of artificial intelligence algorithm that can learn to understand and generate natural language. It is useful for tasks such as language translation, where it takes input text in one language and outputs corresponding text in another language.
The Transformer model consists of two main parts: an encoder and a decoder. The encoder takes the input text and generates a series of numbers that represent the meaning of the text. The decoder then takes those numbers and uses them to generate the output text.