class_docstr: Classifies a set of documents into 1 of N classes.
  
  :param config: A :py:class:`finetune.config.Settings` object or None (for default config).
  :param \**kwargs: key-value pairs of config items to override.
class_docstr_tok: ["Classifies","a","set","of","documents","into","1","of","N","classes",".",":","param","config",":","A",":","py",":","class",":","`","finetune.config.Settings","`","object","or","None","(","for","default","config",")",".",":","param","\\","*","*","kwargs",":","key-value","pairs","of","config","items","to","override","."]
code: def __init__(self, **kwargs):
      d = copy.deepcopy(MultiFieldClassifier.defaults)
      d.update(kwargs)
      super().__init__(**d)
      if self.config.chunk_long_sequences:
          raise FinetuneError(
              "Multifield model is incompatible with chunk_long_sequences = True in config."
          )
  
imports: import copy
  from finetune.errors import FinetuneError
  from finetune.target_models.classifier import Classifier, ClassificationPipeline
  from finetune.target_models.regressor import Regressor, RegressionPipeline
  from finetune.base import BaseModel
label_desc: Use image node_id 1 to create a new MultiFieldClassifier object from inherited base classes: Classifier with example: obj = MultiFieldClassifier()