LSTM input and output for sentiment analysis
Here it looks like the model takes in sequences of words, which are turned into embeddings, which are then put into the LSTM layer. The output of the LSTM layer is a 100 (because this is what is specified in the model) dimensional vector. This 100 dimensional vector is then put into a Dense layer outputting a 1-dimensional object, which I am assuming is some sort of prediction. Does this help? I feel like I may be missing the question.