Attention: Sequence to Sequence Model: Input sequence is provided and output sequence is derived from that input.
Encoder and Decoder: The model encodes a particular input provided by us into something that we call as context vector that is passed to the decoder after the encoding which is then decoded by the help of the decoder.
Now we can always use a big decoder i.e., the output from all the hidden states but then we have performance issues and the chances of overfitting.
