code: def __init__(self, *args, **kwargs):
      if kwargs.get("model") is None and "model" in kwargs:
          kwargs["model"] = "all-MiniLM-L6-v2"
      self.multi_target_strategy = None
      self._column_mapping = None
      ArgillaTransformersTrainer.__init__(self, *args, **kwargs)
  
      if self._record_class is not TextClassificationRecord:
          raise NotImplementedError(
              "SetFit only supports the `TextClassification` task."
          )
  
      if self._multi_label:
          self._column_mapping = {
              "text": "text",
              "binarized_label": "label",
          }
          self.multi_target_strategy = "one-vs-rest"
      else:
          self.multi_target_strategy = None
          self._column_mapping = {"text": "text", "label": "label"}
      self.init_training_args()
  
file_path: argilla/src/argilla/client/feedback/training/frameworks/setfit.py
imports: import logging
  from typing import TYPE_CHECKING
  from argilla.client.feedback.training.frameworks.transformers import ArgillaTransformersTrainer
  from argilla.client.models import TextClassificationRecord
  from argilla.training.setfit import ArgillaSetFitTrainer
  from argilla.utils.dependency import require_dependencies, requires_dependencies
label_desc: Use image node_id 1 to create a new ArgillaSetFitTrainer object from inherited base classes: ArgillaSetFitTrainerV1, ArgillaTransformersTrainer with example: obj = ArgillaSetFitTrainer()