How to Combine tfidf with LSTM in keras?
The goal of text_to_sequence + embedding in traditional LSTM is to transform text to word vectors.

If you already have the tfidf transformation, the idea is usually to get rid of the embedding layer in your LSTM when you are constructing the model, and directly connect the input (i.e., tfidf matrix) to the layer followed by the embedding layer.

Not sure if it's a good approach but that's for you to figure it out :P.