Update app.py

app.py

@@ -14,11 +14,12 @@ def transcribe_audio(audio_bytes):
     model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-large")
     audio_array = np.frombuffer(audio_bytes, dtype=np.int16)
     audio_tensor = torch.tensor(audio_array, dtype=torch.float64) / 32768.0
-    input_values = processor.feature_extractor(audio=audio_tensor, sampling_rate=16000, return_tensors="pt").input_values
+    input_values = processor.feature_extractor(raw_speech=audio_tensor, sampling_rate=16000, return_tensors="pt").input_values
     logits = model(input_values).logits
     predicted_ids = torch.argmax(logits, dim=-1)
     transcription = processor.decode(predicted_ids[0])
     return transcription
+
     
 # Streamlit app
 st.title("Audio to Text Transcription..")