code: def __init__(
      self,
      input_data: List,
      ys: Optional[List],
      keywords: List[str],
  ):
      self._input_data = input_data
      self._ys = ys
      self._keys = keywords
  
file_path: nebuly/optimization/nebullvm/nebullvm/operations/conversions/huggingface.py
imports: from typing import List, Dict, Sequence, Optional
  import numpy
  from nebullvm.core.models import Device
  from nebullvm.optional_modules.tensorflow import tensorflow
  from nebullvm.optional_modules.torch import torch
  from nebullvm.optional_modules.huggingface import PreTrainedTokenizer, PreTrainedModel
  from nebullvm.tools.huggingface import get_output_structure_from_dict, get_output_structure_from_text, PyTorchTransformerWrapper, TensorFlowTransformerWrapper
  from nebullvm.tools.utils import is_dict_type
label_desc: Use image node_id 1 to create a new _HFDictDataset object from inherited base classes: Sequence with example: obj = _HFDictDataset(input_data, ys, keywords)