Upload app.py

app.py

@@ -44,12 +44,12 @@ n_fft, hop_size, win_size = cfg1['stft_cfg']['n_fft'], cfg1['stft_cfg']['hop_siz
 compress_factor = cfg1['model_cfg']['compress_factor']
 sampling_rate = cfg1['stft_cfg']['sampling_rate']
 
-USE_model = SEMamba.from_pretrained("nvidia/RE-USE", cfg=cfg1).to(device)
-USE_model.eval()
-
 @spaces.GPU
 def enhance(filepath, low_pass_sampling_rate, target_sampling_rate): 
     
+    USE_model = SEMamba.from_pretrained("nvidia/RE-USE", cfg=cfg1).to(device)
+    USE_model.eval()
+
     with torch.no_grad():
         noisy_wav, noisy_sr = torchaudio.load(filepath)
         torchaudio.save("original.wav", noisy_wav.cpu(), noisy_sr)