class_docstr: Instantiated Model of the Lemmatizer.
  
  This is the instantiated model of the :class:`.Lemmatizer`.
  For training your own model, please see the documentation of that class.
  
  Pretrained models can be loaded with :meth:`.pretrained` of the companion
  object:
  
  >>> lemmatizer = LemmatizerModel.pretrained() \
  ...     .setInputCols(["token"]) \
  ...     .setOutputCol("lemma")
  
  For available pretrained models please see the `Models Hub <https://sparknlp.org/models?task=Lemmatization>`__.
  
  ====================== ======================
  Input Annotation types Output Annotation type
  ====================== ======================
  ``TOKEN``              ``TOKEN``
  ====================== ======================
  
  Parameters
  ----------
  None
  
  Examples
  --------
  The lemmatizer from the example of the :class:`.Lemmatizer` can be replaced
  with:
  
  >>> lemmatizer = LemmatizerModel.pretrained() \
  ...     .setInputCols(["token"]) \
  ...     .setOutputCol("lemma")
code: def __init__(
      self,
      classname="com.johnsnowlabs.nlp.annotators.LemmatizerModel",
      java_model=None,
  ):
      super(LemmatizerModel, self).__init__(
          classname=classname, java_model=java_model
      )
  
file_path: spark-nlp/python/sparknlp/annotator/lemmatizer.py
imports: from sparknlp.common import *
label_desc: Use image node_id 1 to create a new LemmatizerModel object from inherited base classes: AnnotatorModel with example: obj = LemmatizerModel(classname, java_model)