this approach so that comes the idea of using Engram language models which is hey you just have if you just have a bunch of terms and in a sentence you say that the probability of sentence is probability of individual trans present in it and that's the unigram model but a bigram model is like the problem you you you bet you basically try to say that you take into account the previous word percent in the sentence and say that the probability of a word is conditioned on its previous word and that's saddam v you can start counting pairwise