I want to build a model that takes a document, creates sentence embedding for each sentence using a bi-LSTM, then use the sequence of sentences embedding as input to another bi-LSTM that outputs a probability for each sentence to be a topic shift boundary. I have difficulty building the model, as I never did any custom training before, I am used to considering the whole words as one sequence. Any hints ?


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