class_docstr: Import MOJO Model
class_docstr_tok: ["Import","MOJO","Model"]
docstr: Key to the self-contained model archive already uploaded to H2O.
  
  Type: ``Union[None, str, H2OFrame]``.
  
  :examples:
  
  >>> from h2o.estimators import H2OGenericEstimator, H2OXGBoostEstimator
  >>> import tempfile
  >>> airlines= h2o.import_file("https://s3.amazonaws.com/h2o-public-test-data/smalldata/testng/airlines_train.csv")
  >>> y = "IsDepDelayed"
  >>> x = ["fYear","fMonth","Origin","Dest","Distance"]
  >>> xgb = H2OXGBoostEstimator(ntrees=1, nfolds=3)
  >>> xgb.train(x=x, y=y, training_frame=airlines)
  >>> original_model_filename = tempfile.mkdtemp()
  >>> original_model_filename = xgb.download_mojo(original_model_filename)
  >>> key = h2o.lazy_import(original_model_filename)
  >>> fr = h2o.get_frame(key[0])
  >>> model = H2OGenericEstimator(model_key=fr)
  >>> model.train()
  >>> model.auc()
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code: def model_key(self):
      """
      Key to the self-contained model archive already uploaded to H2O.
  
      Type: ``Union[None, str, H2OFrame]``.
  
      :examples:
  
      >>> from h2o.estimators import H2OGenericEstimator, H2OXGBoostEstimator
      >>> import tempfile
      >>> airlines= h2o.import_file("https://s3.amazonaws.com/h2o-public-test-data/smalldata/testng/airlines_train.csv")
      >>> y = "IsDepDelayed"
      >>> x = ["fYear","fMonth","Origin","Dest","Distance"]
      >>> xgb = H2OXGBoostEstimator(ntrees=1, nfolds=3)
      >>> xgb.train(x=x, y=y, training_frame=airlines)
      >>> original_model_filename = tempfile.mkdtemp()
      >>> original_model_filename = xgb.download_mojo(original_model_filename)
      >>> key = h2o.lazy_import(original_model_filename)
      >>> fr = h2o.get_frame(key[0])
      >>> model = H2OGenericEstimator(model_key=fr)
      >>> model.train()
      >>> model.auc()
      """
      return self._parms.get("model_key")
  
file_path: h2o-3/h2o-py/h2o/estimators/generic.py
imports: from h2o.estimators.estimator_base import H2OEstimator
  from h2o.exceptions import H2OValueError
  from h2o.frame import H2OFrame
  from h2o.utils.typechecks import assert_is_type, Enum, numeric
label_desc: Use image node_id 2 for calling the H2OGenericEstimator obj's underlying member method code with example usage: obj.model_key() and returns: self