docstr: Saves the model to the specified path and optionally generates a `ModelCard` at the same `output_dir`.
  
  Args:
      output_dir: The path to the directory where the model will be saved.
      generate_card: Whether to generate a model card of the `ArgillaTrainer` for the HuggingFace Hub. Defaults
          to `True`.
docstr_tok: ["Saves","the","model","to","the","specified","path","and","optionally","generates","a","`","ModelCard","`","at","the","same","`","output_dir","`",".","Args",":","output_dir",":","The","path","to","the","directory","where","the","model","will","be","saved",".","generate_card",":","Whether","to","generate","a","model","card","of","the","`","ArgillaTrainer","`","for","the","HuggingFace","Hub",".","Defaults","to","`","True","`","."]
code: def save(self, output_dir: str, generate_card: bool = True) -> None:
      """
      Saves the model to the specified path and optionally generates a `ModelCard` at the same `output_dir`.
  
      Args:
          output_dir: The path to the directory where the model will be saved.
          generate_card: Whether to generate a model card of the `ArgillaTrainer` for the HuggingFace Hub. Defaults
              to `True`.
      """
      super().save(output_dir)
  
      if generate_card:
          self.generate_model_card(output_dir)
  
imports: import os
  import textwrap
  import warnings
  from pathlib import Path
  from typing import TYPE_CHECKING, Dict, List, Optional, Union
  from argilla.client.feedback.schemas.records import FeedbackRecord
  from argilla.client.feedback.training.schemas.base import TrainingTaskForTextClassification, TrainingTaskTypes
  from argilla.client.models import Framework, TextClassificationRecord
  from argilla.training.base import ArgillaTrainer
  from argilla.training.base import ArgillaTrainerSkeleton
label_desc: Use image node_id 6 for calling the ArgillaTrainer obj's underlying member method code with example usage: obj.save(output_dir, generate_card) without return types