class_docstr: Abstract base class for a label model implementation.
  
  Args:
      weak_labels: Every label model implementation needs at least a `WeakLabels` instance.
class_docstr_tok: ["Abstract","base","class","for","a","label","model","implementation",".","Args",":","weak_labels",":","Every","label","model","implementation","needs","at","least","a","`","WeakLabels","`","instance","."]
docstr: Fits the label model.
  
  Args:
      include_annotated_records: Whether to include annotated records in the fitting.
docstr_tok: ["Fits","the","label","model",".","Args",":","include_annotated_records",":","Whether","to","include","annotated","records","in","the","fitting","."]
code: def fit(
      self, include_annotated_records: bool = False, *args, **kwargs
  ):
      """Fits the label model.
  
      Args:
          include_annotated_records: Whether to include annotated records in the fitting.
      """
      raise NotImplementedError
  
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 3 for calling the LabelModel obj's underlying member method code with example usage: obj.fit(include_annotated_records) without return types