class_docstr: Word2Vec
class_docstr_tok: ["Word2Vec"]
docstr: Creates new H2OWord2vecEstimator based on an external model.
  
  :param external: H2OFrame with an external model
  :return: H2OWord2vecEstimator instance representing the external model
  
  :examples:
  
  >>> words = h2o.create_frame(rows=10, cols=1,
  ...                          string_fraction=1.0,
  ...                          missing_fraction=0.0)
  >>> embeddings = h2o.create_frame(rows=10, cols=100,
  ...                               real_fraction=1.0,
  ...                               missing_fraction=0.0)
  >>> word_embeddings = words.cbind(embeddings)
  >>> w2v_model = H2OWord2vecEstimator.from_external(external=word_embeddings)
docstr_tok: ["Creates","new","H2OWord2vecEstimator","based","on","an","external","model",".",":","param","external",":","H2OFrame","with","an","external","model",":","return",":","H2OWord2vecEstimator","instance","representing","the","external","model",":","examples",":",">",">",">","words","=","h2o.create_frame","(","rows=10",",","cols=1",",","...","string_fraction=1.0",",","...","missing_fraction=0.0",")",">",">",">","embeddings","=","h2o.create_frame","(","rows=10",",","cols=100",",","...","real_fraction=1.0",",","...","missing_fraction=0.0",")",">",">",">","word_embeddings","=","words.cbind","(","embeddings",")",">",">",">","w2v_model","=","H2OWord2vecEstimator.from_external","(","external=word_embeddings",")"]
code: def from_external(external=H2OFrame):
      """
      Creates new H2OWord2vecEstimator based on an external model.
  
      :param external: H2OFrame with an external model
      :return: H2OWord2vecEstimator instance representing the external model
  
      :examples:
  
      >>> words = h2o.create_frame(rows=10, cols=1,
      ...                          string_fraction=1.0,
      ...                          missing_fraction=0.0)
      >>> embeddings = h2o.create_frame(rows=10, cols=100,
      ...                               real_fraction=1.0,
      ...                               missing_fraction=0.0)
      >>> word_embeddings = words.cbind(embeddings)
      >>> w2v_model = H2OWord2vecEstimator.from_external(external=word_embeddings)
      """
      w2v_model = H2OWord2vecEstimator(pre_trained=external)
      w2v_model.train()
      return w2v_model
  
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 26 for calling the H2OWord2vecEstimator obj's underlying member method code with example usage: obj.from_external(external) and returns: w2v_model