Update app.py

app.py

@@ -70,11 +70,11 @@ def convert_to_wav(filepath):
 pipe = pipeline("automatic-speech-recognition", model="NbAiLab/nb-whisper-large", chunk_length_s=30, generate_kwargs={'task': 'transcribe', 'language': 'no'})
 
 @spaces.GPU()
-def transcribe_audio(audio_file, batch_size=16):
+def transcribe_audio(audio, batch_size=16):
     
     with tempfile.NamedTemporaryFile(suffix=".wav") as temp_audio_file:
         # Copy the contents of the uploaded audio file to the temporary file
-        temp_audio_file.write(open(audio_file, "rb").read())
+        temp_audio_file.write(open(audio, "rb").read())
         temp_audio_file.flush()
         # Load the audio file using torchaudio
         waveform, sample_rate = torchaudio.load(temp_audio_file.name)