parameters: (self, verbose=True)
return_statement: return
docstring: builds a Tamil bigram letter model
docstring_summary: builds a Tamil bigram letter model
docstring_tokens: builds a Tamil bigram letter model
function: def language_model(self, verbose=True):
          """ builds a Tamil bigram letter model """
          # use a generator in corpus
          prev = None
          for next_letter in self.corpus.next_tamil_letter():
              # update frequency from corpus
              if prev:
                  self.letter2[prev][next_letter] += 1
                  if verbose:
                      print(prev)
                      print(next_letter)
                      print(self.letter2[prev][next_letter])
              prev = next_letter  # update always
          return
function_tokens: def language_model ( self , verbose = True ) : # use a generator in corpus prev = None for next_letter in self . corpus . next_tamil_letter ( ) : # update frequency from corpus if prev : self . letter2 [ prev ] [ next_letter ] += 1 if verbose : print ( prev ) print ( next_letter ) print ( self . letter2 [ prev ] [ next_letter ] ) prev = next_letter # update always return