Update README.md

README.md

@@ -13,7 +13,7 @@ It's main use case is providing a low footprint decoder for on-device TTS.
 ```python
 import librosa
 import torch
-import torchaudio
+import soundfile as sf
 from torchaudio import transforms as T
 from neucodec import NeuCodec, NeuCodecOnnxDecoder
  
@@ -29,7 +29,7 @@ with torch.no_grad():
     fsq_codes = model.encode_code(y)
     # fsq_codes = model.encode_code(librosa.ex("libri1")) # or directly pass your filepath!
     print(f"Codes shape: {fsq_codes.shape}")  
-    recon = compiled_model.decode_code(fsq_codes).cpu() # (B, 1, T_24)
+    recon = compiled_model.decode_code(fsq_codes) # (B, 1, T_24)
 
-torchaudio.save("reconstructed.wav", recon[0, :, :], 24_000)
+sf.write("reconstructed.wav", recon, 24_000)
 ```