Now we process the audio data, pass the processed audio data to the model and transcribe the model output,
just like we usually do for [Wav2Vec2ForCTC].

inputs = processor(en_sample, sampling_rate=16_000, return_tensors="pt")
with torch.no_grad():
    outputs = model(**inputs).logits
ids = torch.argmax(outputs, dim=-1)[0]
transcription = processor.decode(ids)
'joe keton disapproved of films and buster also had reservations about the media'