class_docstr: A basic label model that computes the majority vote across all rules.
  
  For single-label classification, it will predict the label with the most votes.
  For multi-label classification, it will predict all labels that got at least one vote by the rules.
  
  Args:
      weak_labels: The weak labels object.
class_docstr_tok: ["A","basic","label","model","that","computes","the","majority","vote","across","all","rules",".","For","single-label","classification",",","it","will","predict","the","label","with","the","most","votes",".","For","multi-label","classification",",","it","will","predict","all","labels","that","got","at","least","one","vote","by","the","rules",".","Args",":","weak_labels",":","The","weak","labels","object","."]
code: def __init__(self, weak_labels: Union[WeakLabels, WeakMultiLabels]):
      super().__init__(weak_labels=weak_labels)
  
imports: import hashlib
  import logging
  from enum import Enum
  from typing import Dict, List, Tuple, Union
  import numpy
  from argilla import DatasetForTextClassification, TextClassificationRecord
  from argilla.labeling.text_classification.weak_labels import WeakLabels, WeakMultiLabels
  from argilla.utils.dependency import requires_dependencies
label_desc: Use image node_id 1 to create a new MajorityVoter object from inherited base classes: LabelModel with example: obj = MajorityVoter(weak_labels)