What is the correct sequence of steps in the process of using a sequence transduction model for translating input sequences into output sequences?

To translate input sequences into output sequences with a sequence transduction model, you first encode the input string into a continuous representation using an encoder, such as a recurrent or transformer network. Next, the decoder begins generating the output one token at a time, conditioning on the encoder’s representation and all previously generated tokens. During training, the model learns to predict each next token by minimizing the difference between its prediction and the true target token. After training, you run inference by feeding the encoder the new input, then let the decoder produce the translated sequence, often using greedy search or beam search to pick the most likely tokens. For example, translating “cat” to French would involve encoding the English word, then decoding step by step to output “chat”.