code: def load_bettertransformer(
      model,
      targeted_task,
      load_tokenizer=None,
      tokenizer=None,
      feature_extractor=None,
      load_feature_extractor=None,
      SUPPORTED_TASKS=None,
      subfolder: str = "",
      token: Optional[Union[bool, str]] = None,
      revision: str = "main",
      model_kwargs: Optional[Dict[str, Any]] = None,
      config: AutoConfig = None,
      hub_kwargs: Optional[Dict] = None,
      **kwargs,
  ):
      if model_kwargs is None:
          model_kwargs = {}
  
      if model is None:
          model_id = SUPPORTED_TASKS[targeted_task]["default"]
      elif isinstance(model, str):
          model_id = model
      else:
          model_id = None
  
      model_classes = {"pt": SUPPORTED_TASKS[targeted_task]["pt"]}
      framework, model = infer_framework_load_model(
          model,
          model_classes=model_classes,
          config=config,
          framework="pt",
          task=targeted_task,
          **hub_kwargs,
          **model_kwargs,
      )
  
      if framework == "tf":
          raise NotImplementedError(
              "BetterTransormer is PyTorch-specific. It will not work with the provided TensorFlow model."
          )
  
      model = BetterTransformer.transform(model, **kwargs)
  
      return model, model_id, tokenizer, feature_extractor
  
file_path: optimum/optimum/pipelines/pipelines_base.py
imports: from typing import Any, Dict, Optional, Union
  from transformers import AudioClassificationPipeline, AutoConfig, AutomaticSpeechRecognitionPipeline, FeatureExtractionPipeline, FillMaskPipeline, ImageClassificationPipeline, ImageSegmentationPipeline, ImageToTextPipeline, Pipeline, PreTrainedTokenizer, PreTrainedTokenizerFast, QuestionAnsweringPipeline, SequenceFeatureExtractor, SummarizationPipeline, Text2TextGenerationPipeline, TextClassificationPipeline, TextGenerationPipeline, TokenClassificationPipeline, TranslationPipeline, ZeroShotClassificationPipeline
  from transformers import pipeline
  from transformers.feature_extraction_utils import PreTrainedFeatureExtractor
  from transformers.onnx.utils import get_preprocessor
  from transformers.pipelines import SUPPORTED_TASKS
  from transformers.pipelines import infer_framework_load_model
  from ..bettertransformer import BetterTransformer
  from ..utils import is_onnxruntime_available
  from ..utils.file_utils import find_files_matching_pattern
label_desc: Use image node_id 1 for calling a global function with example usage: load_bettertransformer(model, targeted_task, load_tokenizer, tokenizer, feature_extractor, load_feature_extractor, SUPPORTED_TASKS, subfolder, token, revision, model_kwargs, config, hub_kwargs) and returns: model,  model_id,  tokenizer,  feature_extractor