Update app.py

app.py

@@ -15,9 +15,9 @@ import torchaudio
 from torchaudio import transforms as T
 from neucodec import DistillNeuCodec
 
-# Load model
+# Load model on CPU
 model = DistillNeuCodec.from_pretrained("neuphonic/distill-neucodec")
-model.eval().cuda()
+model.eval()  # CPU only
 
 def reconstruct_audio(audio_file):
     # Load uploaded audio
@@ -28,10 +28,10 @@ def reconstruct_audio(audio_file):
         y = T.Resample(sr, 16_000)(y)
     y = y[None, ...]  # Add batch dim (B, 1, T)
     
-    # Encode and decode
+    # Encode and decode on CPU
     with torch.no_grad():
-        fsq_codes = model.encode_code(y.cuda())
-        recon = model.decode_code(fsq_codes).cpu()
+        fsq_codes = model.encode_code(y)
+        recon = model.decode_code(fsq_codes)
     
     # Save to temporary file
     recon_path = "reconstructed.wav"
@@ -44,8 +44,8 @@ iface = gr.Interface(
     fn=reconstruct_audio,
     inputs=gr.Audio(type="filepath", label="Upload Audio"),
     outputs=gr.Audio(type="filepath", label="Reconstructed Audio"),
-    title="Audio Reconstruction with DistillNeuCodec",
-    description="Upload any audio file, and this app will reconstruct it using DistillNeuCodec at 24kHz."
+    title="Audio Reconstruction with DistillNeuCodec (CPU)",
+    description="Upload any audio file, and this app will reconstruct it using DistillNeuCodec at 24kHz on CPU."
 )
 
 if __name__ == "__main__":