I want to use the Glove vectors in Language Modeling. But the problem is if I use Embedding layer in the model, I can't predict the output vector and match the word. What I mean here is, I want to give the glove vector representation for my sentences as the Input. and get them out from the Lstm layer and get the vectors and match it with Glove vectors I want to use the glove vectors without embedding layer. can someone propose a method to do it? I am using the keras and python3
What I want is to use the embedding layer as one model1 and return the output vector and give it to another LSTM model2 as the input. where it gives the index of the word vector.
