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Neural network primarily based language models simplicity the sparsity dilemma Incidentally they encode inputs. Term embedding layers make an arbitrary sized vector of each phrase that comes with semantic relationships at the same time. These continuous vectors develop the A great deal required granularity from the probability distribution of the f