An encoder-decoder architecture is a powerful tool used in machine learning, specifically for tasks involving sequences like text or speech. It’s like a two-part machine that translates one form ...

The decoder then generates the output sequence one token at a time, using both the encoder’s representations and the previously generated tokens to inform the context, allowing it to consider ...

Seq2Seq models are a type of neural network architecture specifically designed to process and generate sequences. They consist of two main components: an encoder and a decoder.