Update README.md

README.md

@@ -27,10 +27,10 @@ To transcribe audio files the model can be used as a standalone acoustic model a
  processor = Wav2Vec2Processor.from_pretrained("sanchit-gandhi/wav2vec2-large-tedlium")
  model = Wav2Vec2ForCTC.from_pretrained("sanchit-gandhi/wav2vec2-large-tedlium")
      
- # load dummy dataset and read soundfiles
+ # load dummy dataset
  ds = load_dataset("sanchit-gandhi/tedlium_dummy", split="validation")
  
- # tokenize
+ # process audio inputs
  input_values = processor(ds[0]["audio"]["array"], return_tensors="pt", padding="longest").input_values  # Batch size 1
  
  # retrieve logits