class_docstr: Represents the source of a Hugging Face dataset used in MLflow Tracking.
docstr: Load the Hugging Face dataset based on `HuggingFaceDatasetSource`.
  
  Args:
      kwargs: Additional keyword arguments used for loading the dataset with the Hugging Face
          `datasets.load_dataset()` method.
  
  Returns:
      An instance of `datasets.Dataset`.
code: def load(self, **kwargs):
      """Load the Hugging Face dataset based on `HuggingFaceDatasetSource`.
  
      Args:
          kwargs: Additional keyword arguments used for loading the dataset with the Hugging Face
              `datasets.load_dataset()` method.
  
      Returns:
          An instance of `datasets.Dataset`.
      """
      import datasets
  
      load_kwargs = {
          "path": self.path,
          "name": self.config_name,
          "data_dir": self.data_dir,
          "data_files": self.data_files,
          "split": self.split,
          "revision": self.revision,
      }
      intersecting_keys = set(load_kwargs.keys()) & set(kwargs.keys())
      if intersecting_keys:
          raise KeyError(
              f"Found duplicated arguments in `HuggingFaceDatasetSource` and "
              f"`kwargs`: {intersecting_keys}. Please remove them from `kwargs`."
          )
          load_kwargs.update(kwargs)
      return datasets.load_dataset(**load_kwargs)
  
file_path: mlflow/mlflow/data/huggingface_dataset_source.py
imports: from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Sequence, Union
  from mlflow.data.dataset_source import DatasetSource
  from mlflow.utils.annotations import experimental
label_desc: Use image node_id 3 for calling the HuggingFaceDatasetSource obj's underlying member method code with example usage: obj.load() and returns: datasets