code: def fit(self, X, y):
          
          trainer = pycrfsuite.Trainer(verbose=True)
          for xseq, yseq in zip(X, y):
              trainer.append(xseq, yseq)
  
          trainer.set_params(self.params)
          if self.filename:
              filename = self.filename
          else:
              filename = 'model.tmp'
          trainer.train(filename)
          tagger = pycrfsuite.Tagger()
          tagger.open(filename)
          self.estimator = tagger
docs: Fit CRF according to X, y
  
          Parameters
          ----------
          X : list of text
              each item is a text
          y: list
             each item is either a label (in multi class problem) or list of
             labels (in multi label problem)