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")
docstr: Downloads and loads a pretrained model.
  
  Parameters
  ----------
  name : str, optional
      Name of the pretrained model, by default "lemma_antbnc"
  lang : str, optional
      Language of the pretrained model, by default "en"
  remote_loc : str, optional
      Optional remote address of the resource, by default None. Will use
      Spark NLPs repositories otherwise.
  
  Returns
  -------
  LemmatizerModel
      The restored model
code: def pretrained(name="lemma_antbnc", lang="en", remote_loc=None):
      """Downloads and loads a pretrained model.
  
      Parameters
      ----------
      name : str, optional
          Name of the pretrained model, by default "lemma_antbnc"
      lang : str, optional
          Language of the pretrained model, by default "en"
      remote_loc : str, optional
          Optional remote address of the resource, by default None. Will use
          Spark NLPs repositories otherwise.
  
      Returns
      -------
      LemmatizerModel
          The restored model
      """
      from sparknlp.pretrained import ResourceDownloader
  
      return ResourceDownloader.downloadModel(
          LemmatizerModel, name, lang, remote_loc
      )
  
file_path: spark-nlp/python/sparknlp/annotator/lemmatizer.py
imports: from sparknlp.common import *
label_desc: Use image node_id 2 for calling the LemmatizerModel obj's underlying member method code with example usage: obj.pretrained(name, lang, remote_loc) and returns: ResourceDownloader