class_docstr: Loader that loads the transcriptions of audio
code: def __init__(
      self,
      path_audios: Union[str, List[str]] = None,
      asr_model="openai/whisper-medium",
      asr_gpu=True,
      gpu_id="auto",
      use_better=True,
      use_faster=False,
  ):
      super().__init__(path_audios)
      self.audio_paths = path_audios
      self.model = None
      self.asr_model = asr_model
      self.asr_gpu = asr_gpu
      self.context_class = NullContext
      self.gpu_id = gpu_id if isinstance(gpu_id, int) else 0
      self.device = "cpu"
      self.device_map = {"": "cpu"}
      self.set_context()
      self.use_better = use_better
      self.use_faster = use_faster
      self.files_out = []
  
imports: import logging
  import os
  import tempfile
  import time
  from typing import Dict, Iterator, Optional, Tuple
  from langchain.document_loaders.base import BaseBlobParser
  from langchain.document_loaders.blob_loaders import Blob
  from langchain.document_loaders.generic import GenericLoader
  from langchain.schema import Document
  from typing import List, Union, Any, Tuple
  import requests
  from langchain.docstore.document import Document
  from langchain.document_loaders import ImageCaptionLoader
  from utils import get_device, NullContext, clear_torch_cache, have_use_faster, makedirs
  from importlib.metadata import distribution, PackageNotFoundError
  from typing import Iterable, List
  from langchain.document_loaders.blob_loaders import FileSystemBlobLoader
  from langchain.document_loaders.blob_loaders.schema import Blob, BlobLoader
label_desc: Use image node_id 1 to create a new H2OAudioCaptionLoader object from inherited base classes: ImageCaptionLoader with example: obj = H2OAudioCaptionLoader(path_audios, asr_model, asr_gpu, gpu_id, use_better, use_faster)