Solved by vdw in post #2 
              
              
                Maybe I misunderstand something wrong, but I think nothing should change when using pretrained word embeddings. When your dataset has a vocabulary of size 20k, you only need the 20k respective word embeddings. 
An embedding layer is essentially just a look-up layer. So there is no need for embedding…