Update app.py

app.py

@@ -57,17 +57,17 @@ class SpeechClassifier(nn.Module, PyTorchModelHubMixin):
 
 # Prepare data function
 def prepare_data(audio_data, sampling_rate, model_checkpoint="openai/whisper-base"):
-    
+
     # Resample audio data to 16000 Hz
     audio_data_resampled = librosa.resample(audio_data, orig_sr=sampling_rate, target_sr=16000)
 
     # Initialize the feature extractor
     feature_extractor = WhisperFeatureExtractor.from_pretrained(model_checkpoint)
-    
-    # Use Dataset class 
+
+    # Use Dataset class
     dataset = SpeechInferenceDataset([{"audio": {"array": audio_data_resampled, "sampling_rate": 16000}}],
                                      text_processor=feature_extractor)
-    
+
     return dataset
 
 
@@ -119,5 +119,5 @@ with gr.Blocks() as demo:
             outputs=gr.Textbox(label="Prediction")
         )
 
-# Launch the demo with debugging enabled
-demo.launch(debug=True)
+# Launch the demo
+demo.launch()