code: def load_model(self, fname):
          
          if self._Booster is None:
              self._Booster = Booster({'nthread': self.n_jobs})
          self._Booster.load_model(fname)
docs: Load the model from a file.
  
          The model is loaded from an XGBoost internal binary format which is
          universal among the various XGBoost interfaces. Auxiliary attributes of
          the Python Booster object (such as feature names) will not be loaded.
          Label encodings (text labels to numeric labels) will be also lost.
          **If you are using only the Python interface, we recommend pickling the
          model object for best results.**
  
          Parameters
          ----------
          fname : string or a memory buffer
              Input file name or memory buffer(see also save_raw)