class_docstr: Handles Amazon SageMaker processing tasks for jobs using HuggingFace containers.
class_docstr_tok: ["Handles","Amazon","SageMaker","processing","tasks","for","jobs","using","HuggingFace","containers","."]
docstr: Override default estimator factory function for HuggingFace's different parameters
  
  HuggingFace estimators have 3 framework version parameters instead of one: The version for
  Transformers, PyTorch, and TensorFlow.
docstr_tok: ["Override","default","estimator","factory","function","for","HuggingFace","'s","different","parameters","HuggingFace","estimators","have","3","framework","version","parameters","instead","of","one",":","The","version","for","Transformers",",","PyTorch",",","and","TensorFlow","."]
code: def _create_estimator(
      self,
      entry_point="",
      source_dir=None,
      dependencies=None,
      git_config=None,
  ):
      """Override default estimator factory function for HuggingFace's different parameters
  
      HuggingFace estimators have 3 framework version parameters instead of one: The version for
      Transformers, PyTorch, and TensorFlow.
      """
      return self.estimator_cls(
          transformers_version=self.framework_version,
          tensorflow_version=self.tensorflow_version,
          pytorch_version=self.pytorch_version,
          py_version=self.py_version,
          entry_point=entry_point,
          source_dir=source_dir,
          dependencies=dependencies,
          git_config=git_config,
          code_location=self.code_location,
          enable_network_isolation=False,
          image_uri=self.image_uri,
          role=self.role,
          instance_count=self.instance_count,
          instance_type=self.instance_type,
          sagemaker_session=self.sagemaker_session,
          debugger_hook_config=False,
          disable_profiler=True,
      )
  
file_path: sagemaker-python-sdk/src/sagemaker/huggingface/processing.py
imports: from __future__ import absolute_import
  from typing import Union, Optional, List, Dict
  from sagemaker.session import Session
  from sagemaker.network import NetworkConfig
  from sagemaker.processing import FrameworkProcessor
  from sagemaker.huggingface.estimator import HuggingFace
  from sagemaker.workflow.entities import PipelineVariable
  from sagemaker.utils import format_tags, Tags
label_desc: Use image node_id 2 for calling the HuggingFaceProcessor obj's underlying member method code with example usage: obj._create_estimator(entry_point, source_dir, dependencies, git_config) and returns: self