docstr: Pushes the `FeedbackDataset` to the Hugging Face Hub. If the dataset has been previously pushed to the
  Hugging Face Hub, it will be updated instead. Note that some params as `private` have no effect at all
  when a dataset is previously uploaded to the Hugging Face Hub.
  
  Args:
      dataset: the `FeedbackDataset` to push to the Hugging Face Hub.
      repo_id: the ID of the Hugging Face Hub repo to push the `FeedbackDataset` to.
      generate_card: whether to generate a dataset card for the `FeedbackDataset` in the Hugging Face Hub. Defaults
          to `True`.
      *args: the args to pass to `datasets.Dataset.push_to_hub`.
      **kwargs: the kwargs to pass to `datasets.Dataset.push_to_hub`.
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code: def push_to_huggingface(
      self: "FeedbackDataset",
      repo_id: str,
      generate_card: Optional[bool] = True,
      *args,
      **kwargs,
  ) -> None:
      """Pushes the `FeedbackDataset` to the Hugging Face Hub. If the dataset has been previously pushed to the
      Hugging Face Hub, it will be updated instead. Note that some params as `private` have no effect at all
      when a dataset is previously uploaded to the Hugging Face Hub.
  
      Args:
          dataset: the `FeedbackDataset` to push to the Hugging Face Hub.
          repo_id: the ID of the Hugging Face Hub repo to push the `FeedbackDataset` to.
          generate_card: whether to generate a dataset card for the `FeedbackDataset` in the Hugging Face Hub. Defaults
              to `True`.
          *args: the args to pass to `datasets.Dataset.push_to_hub`.
          **kwargs: the kwargs to pass to `datasets.Dataset.push_to_hub`.
      """
      import huggingface_hub
      from huggingface_hub import HfApi
  
      # https://github.com/argilla-io/argilla/issues/3468
      from argilla.client.feedback.config import DatasetConfig
  
      if parse_version(huggingface_hub.__version__) < parse_version(
          "0.14.0"
      ):
          _LOGGER.warning(
              "Recommended `huggingface_hub` version is 0.14.0 or higher, and you have"
              f" {huggingface_hub.__version__}, so in case you have any issue when pushing the dataset to the"
              " Hugging Face Hub upgrade it as `pip install huggingface_hub --upgrade`."
          )
  
      if len(self) < 1:
          raise ValueError(
              "Cannot push an empty `rg.FeedbackDataset` to the Hugging Face Hub, please make sure to add at"
              " least one record, via the method `add_records`."
          )
  
      hfds = self.format_as("datasets")
      hfds.push_to_hub(repo_id, *args, **kwargs)
  
      with tempfile.NamedTemporaryFile(mode="w", delete=False) as f:
          f.write(
              DatasetConfig(
                  fields=self.fields,
                  questions=self.questions,
                  guidelines=self.guidelines,
                  metadata_properties=self.metadata_properties or None,
                  allow_extra_metadata=self.allow_extra_metadata,
                  vectors_settings=self.vectors_settings or None,
              ).to_yaml()
          )
          f.flush()
  
          HfApi().upload_file(
              path_or_fileobj=f.name,
              path_in_repo="argilla.yaml",
              repo_id=repo_id,
              repo_type="dataset",
              token=kwargs.get("token"),
          )
  
      if generate_card:
          from huggingface_hub import DatasetCardData
  
          from argilla.client.feedback.integrations.huggingface.card import (
              ArgillaDatasetCard,
              size_categories_parser,
          )
  
          sample_argilla_record = self.records[0]
          sample_argilla_record = (
              sample_argilla_record.to_local()
              if isinstance(sample_argilla_record, RemoteFeedbackRecord)
              else sample_argilla_record
          )
          sample_huggingface_record = hfds[0]
  
          card = ArgillaDatasetCard.from_template(
              card_data=DatasetCardData(
                  size_categories=size_categories_parser(
                      len(self.records)
                  ),
                  tags=["rlfh", "argilla", "human-feedback"],
              ),
              repo_id=repo_id,
              argilla_fields=self.fields,
              argilla_questions=self.questions,
              argilla_guidelines=self.guidelines or None,
              argilla_vectors_settings=self.vectors_settings or None,
              argilla_metadata_properties=self.metadata_properties,
              argilla_record=json.loads(sample_argilla_record.json()),
              huggingface_record=sample_huggingface_record,
          )
          card.push_to_hub(
              repo_id, repo_type="dataset", token=kwargs.get("token")
          )
  
file_path: argilla/src/argilla/client/feedback/integrations/huggingface/dataset.py
imports: import json
  import logging
  import tempfile
  import warnings
  from typing import TYPE_CHECKING, Any, Optional, Type, Union
  from packaging.version import parse
  from tqdm import trange
  from argilla.client.feedback.constants import FIELD_TYPE_TO_PYTHON_TYPE
  from argilla.client.feedback.schemas.enums import QuestionTypes
  from argilla.client.feedback.schemas.records import FeedbackRecord
  from argilla.client.feedback.schemas.remote.records import RemoteFeedbackRecord
  from argilla.utils.dependency import requires_dependencies
label_desc: Use image node_id 2 for calling the HuggingFaceDatasetMixin obj's underlying member method code with example usage: obj.push_to_huggingface(repo_id, generate_card) without return types