I am looking into seq2seq model in keras, for example, this blog post from keras or this. All the examples I have seen have some inference model, that depicts the original model. That inference model is then used to make the predictions.
My question is why can't we just do the
model.predict(). I mean, we can because I have used it and it works but what is the difference between these two approaches. Is it wrong to use
model.predict() and do the reverse word tokenizer for the argmax ?