Do I need an encoder-decoder architecture to predict the next item of a sequence?

I am trying to understand how RNNs are used for sequence modelling.

On a tutorial here, it mentions that if you want to translate say a sentence from English to French you can use an encoder-decoder set-up as they described.

However what if you want to do a sequence to sequence modelling where your inputs and outputs are of the same domain but you just want to predict the next output of a sequence.

For example if I want to use sequence modelling to learn the sine function. So say I have 20 y-coordinates from $$y = sin(x)$$ from 20 evenly spaced out x-coordinates and I want to predict the next 10 or so y-coordinates. Would I use an encoder-decoder setup here?