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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def train(self, sentences, model):
 """Train the CRF tagger using CRFSuite. :params sentences: Annotated sentences. :params model: Path to save pickled model. """

        trainer = pycrfsuite.Trainer(verbose=True)
        trainer.set_params(self.params)
        for sentence in sentences:
            tokens, labels = zip(*sentence)
            features = [self._get_features(tokens, i) for i in range(len(tokens))]
            trainer.append(features, labels)
        trainer.train(model)
        self.load(model)