docstr: Handle HuggingFace functions
  
  HuggingFace functions are special functions that are not loaded from a file.
  So we do not need to call the setup method on them like we do for other functions.
docstr_tok: ["Handle","HuggingFace","functions","HuggingFace","functions","are","special","functions","that","are","not","loaded","from","a","file",".","So","we","do","not","need","to","call","the","setup","method","on","them","like","we","do","for","other","functions","."]
code: def handle_huggingface_function(self):
      """Handle HuggingFace functions
  
      HuggingFace functions are special functions that are not loaded from a file.
      So we do not need to call the setup method on them like we do for other functions.
      """
      # We need at least one deep learning framework for HuggingFace
      # Torch or Tensorflow
      try_to_import_torch()
      impl_path = (
          f"{self.function_dir}/abstract/hf_abstract_function.py"
      )
      io_list = gen_hf_io_catalog_entries(
          self.node.name, self.node.metadata
      )
      return (
          self.node.name,
          impl_path,
          self.node.function_type,
          io_list,
          self.node.metadata,
      )
  
imports: import contextlib
  import hashlib
  import locale
  import os
  import pickle
  import re
  import time
  from pathlib import Path
  from typing import Dict, List
  import numpy
  import pandas
  from evadb.catalog.catalog_utils import get_metadata_properties
  from evadb.catalog.models.function_catalog import FunctionCatalogEntry
  from evadb.catalog.models.function_io_catalog import FunctionIOCatalogEntry
  from evadb.catalog.models.function_metadata_catalog import FunctionMetadataCatalogEntry
  from evadb.configuration.constants import DEFAULT_SKLEARN_TRAIN_MODEL, DEFAULT_TRAIN_REGRESSION_METRIC, DEFAULT_TRAIN_TIME_LIMIT, DEFAULT_XGBOOST_TASK, SKLEARN_SUPPORTED_MODELS, EvaDB_INSTALLATION_DIR
  from evadb.database import EvaDBDatabase
  from evadb.executor.abstract_executor import AbstractExecutor
  from evadb.functions.decorators.utils import load_io_from_function_decorators
  from evadb.models.storage.batch import Batch
  from evadb.plan_nodes.create_function_plan import CreateFunctionPlan
  from evadb.third_party.huggingface.create import gen_hf_io_catalog_entries
  from evadb.utils.errors import FunctionIODefinitionError
  from evadb.utils.generic_utils import load_function_class_from_file, string_comparison_case_insensitive, try_to_import_flaml_automl, try_to_import_ludwig, try_to_import_neuralforecast, try_to_import_statsforecast, try_to_import_torch, try_to_import_ultralytics
  from evadb.utils.logging_manager import logger
label_desc: Use image node_id 2 for calling the CreateFunctionExecutor obj's underlying member method code with example usage: obj.handle_huggingface_function() and returns: self,  impl_path,  self,  io_list,  self