class_docstr: Tokenizes raw text into word pieces, tokens. Identifies tokens with
  tokenization open standards. A few rules will help customizing it if
  defaults do not fit user needs.
  
  This class represents an already fitted :class:`.Tokenizer`.
  
  See the main class Tokenizer for more examples of usage.
  
  ======================  ======================
  Input Annotation types  Output Annotation type
  ======================  ======================
  ``DOCUMENT``            ``TOKEN``
  ======================  ======================
  
  Parameters
  ----------
  splitPattern
      Character list used to separate from the inside of tokens
  splitChars
      Character list used to separate from the inside of tokens
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docstr: Downloads and loads a pretrained model.
  
  Parameters
  ----------
  name : str, optional
      Name of the pretrained model, by default "token_rules"
  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
  -------
  TokenizerModel
      The restored model
docstr_tok: ["Downloads","and","loads","a","pretrained","model",".","Parameters","--","--","--","--","--","name",":","str",",","optional","Name","of","the","pretrained","model",",","by","default","``","token_rules","''","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","--","--","--","-","TokenizerModel","The","restored","model"]
code: def pretrained(name="token_rules", lang="en", remote_loc=None):
      """Downloads and loads a pretrained model.
  
      Parameters
      ----------
      name : str, optional
          Name of the pretrained model, by default "token_rules"
      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
      -------
      TokenizerModel
          The restored model
      """
      from sparknlp.pretrained import ResourceDownloader
  
      return ResourceDownloader.downloadModel(
          TokenizerModel, name, lang, remote_loc
      )
  
imports: from sparknlp.common import *
label_desc: Use image node_id 5 for calling the TokenizerModel obj's underlying member method code with example usage: obj.pretrained(name, lang, remote_loc) and returns: ResourceDownloader