code: def run_hf_repo_single_node(run_options):
      """Test function for basic HF model use.
  
      Arguments
      ---------
  
      run_options: dict
          A set of options to change the runtime environment.
      """
      # Test on both nodes w/ pretrained HF model; ensure first it's fetched
      repo = FetchSource(
          FetchFrom.HUGGING_FACE,  # needs to be here only bc local path "speechbrain/asr-crdnn-rnnlm-librispeech" exists
          "speechbrain/asr-crdnn-rnnlm-librispeech",
      )
      EncoderDecoderASR.from_hparams(
          source=repo,  # to default save_dir: pretrained_models/...
          download_only=True,
      )
  
      # Instantiate pretrained HF model
      pretrained_hf_asr = EncoderDecoderASR.from_hparams(
          source=repo,
          run_opts=deepcopy(run_options),
      )
  
      # From HF model card
      pred = pretrained_hf_asr.transcribe_file(
          FetchSource(
              FetchFrom.HUGGING_FACE,  # bc HF-alike local path structure exists
              "speechbrain/asr-crdnn-rnnlm-librispeech/example.wav",
          )
      )
  
      print(f"prediction: {pred}")
  
imports: import logging
  import speechbrain
  from copy import deepcopy
  from speechbrain.inference.ASR import EncoderDecoderASR
  from speechbrain.utils.fetching import FetchFrom, FetchSource
label_desc: Use image node_id 1 for calling a global function with example usage: run_hf_repo_single_node(run_options) without return types