code: def tag(self, tokens):
          
          # Lazy load model first time we tag
          if not self.classes:
              self.load(self.model)
          prev, prev2 = self.START
          tags = []
          for i, token in enumerate(tokens):
              tag = self.tagdict.get(token)
              if not tag:
                  features = self._get_features(i, tokens, prev, prev2)
                  tag = self.perceptron.predict(features)
              tags.append((token, tag))
              prev2 = prev
              prev = tag
          return tags
docs: Return a list of (token, tag) tuples for a given list of tokens.