class_docstr: Sentiment analyser inspired by the algorithm by Vivek Narayanan.
  
  This is the instantiated model of the :class:`.ViveknSentimentApproach`. For
  training your own model, please see the documentation of that class.
  
  The analyzer requires sentence boundaries to give a score in context.
  Tokenization is needed to make sure tokens are within bounds. Transitivity
  requirements are also required.
  
  For extended examples of usage, see the `Examples
  <https://github.com/JohnSnowLabs/spark-nlp/blob/master/examples/python/training/english/vivekn-sentiment/VivekNarayanSentimentApproach.ipynb>`__.
  
  ====================== ======================
  Input Annotation types Output Annotation type
  ====================== ======================
  ``TOKEN, DOCUMENT``    ``SENTIMENT``
  ====================== ======================
  
  Parameters
  ----------
  None
  
  References
  ----------
  The algorithm is based on the paper `"Fast and accurate sentiment
  classification using an enhanced Naive Bayes model"
  <https://arxiv.org/abs/1305.6143>`__.
  
  https://github.com/vivekn/sentiment/
docstr: Downloads and loads a pretrained model.
  
  Parameters
  ----------
  name : str, optional
      Name of the pretrained model, by default "sentiment_vivekn"
  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
  -------
  ViveknSentimentModel
      The restored model
code: def pretrained(name="sentiment_vivekn", lang="en", remote_loc=None):
      """Downloads and loads a pretrained model.
  
      Parameters
      ----------
      name : str, optional
          Name of the pretrained model, by default "sentiment_vivekn"
      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
      -------
      ViveknSentimentModel
          The restored model
      """
      from sparknlp.pretrained import ResourceDownloader
  
      return ResourceDownloader.downloadModel(
          ViveknSentimentModel, name, lang, remote_loc
      )
  
file_path: spark-nlp/python/sparknlp/annotator/sentiment/vivekn_sentiment.py
imports: from sparknlp.common import *
  from sparknlp.common.annotator_type import AnnotatorType
label_desc: Use image node_id 2 for calling the ViveknSentimentModel obj's underlying member method code with example usage: obj.pretrained(name, lang, remote_loc) and returns: ResourceDownloader