Update app.py

app.py

@@ -24,7 +24,7 @@ TARGET_SAMPLE_RATE = 16000
 model = TinyVAD(1, 32, 64, patch_size=8, num_blocks=2, 
                 sinc_conv=SINC_CONV, ssm=SSM)
 checkpoint_path = './sincvad.ckpt'
-checkpoint = torch.load(checkpoint_path, map_location=torch.device('cpu'))
+checkpoint = torch.load(checkpoint_path, map_location=torch.device('cpu'), weights_only=True)
 model.load_state_dict(checkpoint, strict=False)
 model.eval()
 
@@ -173,8 +173,8 @@ with gr.Blocks() as demo:
     with gr.Row():
         with gr.Column():
             # Separate recording and file upload
-            record_input = gr.Audio(source="microphone", type="filepath", label="Record Audio")
-            upload_input = gr.Audio(source="upload", type="filepath", label="Upload Audio")
+            record_input = gr.Audio(sources="microphone", type="filepath", label="Record Audio")
+            upload_input = gr.Audio(sources="upload", type="filepath", label="Upload Audio")
             threshold_input = gr.Slider(minimum=0, maximum=1, value=0.5, step=0.1, label="Threshold")
         with gr.Column():
             prediction_output = gr.Textbox(label="Prediction")