class_docstr: An abstract class for all HuggingFace models.
  
  This is implemented using the pipeline API from HuggingFace. pipeline is an
  easy way to use a huggingface model for inference. In EvaDB, we require users
  to mention the task they want to perform for simplicity. A HuggingFace task
  is different from a model(pytorch). There are a large number of models on HuggingFace
  hub that can be used for a particular task. The user can specify the model or a default
  model will be used.
  
  Refer to https://huggingface.co/transformers/main_classes/pipelines.html for more details
  on pipelines.
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docstr: Arguments that will be passed to the pipeline by default.
  User provided arguments override the default arguments
docstr_tok: ["Arguments","that","will","be","passed","to","the","pipeline","by","default",".","User","provided","arguments","override","the","default","arguments"]
code: def default_pipeline_args(self) -> dict:
      """
      Arguments that will be passed to the pipeline by default.
      User provided arguments override the default arguments
      """
      return {}
  
file_path: evadb/evadb/functions/abstract/hf_abstract_function.py
imports: from typing import Any
  import pandas
  from evadb.catalog.models.function_catalog import FunctionCatalogEntry
  from evadb.functions.abstract.abstract_function import AbstractFunction
  from evadb.functions.gpu_compatible import GPUCompatible
  from evadb.utils.generic_utils import try_to_import_transformers
label_desc: Use image node_id 4 for calling the AbstractHFFunction obj's underlying member method code with example usage: obj.default_pipeline_args() and returns: dict