Update app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 from transformers import MusicGenForConditionalGeneration, MusicGenProcessor
 import torch
+import soundfile as sf  # For saving audio as WAV
 
 # Load the MusicGen model and processor
 model_name = "facebook/musicgen-small"
@@ -14,11 +15,14 @@ def generate_audio(text):
 
     # Generate audio (samples)
     with torch.no_grad():
-        generated_audio = model.generate_audio(**inputs)
+        generated_audio = model.generate(**inputs)
 
-    # Save the generated audio
+    # Convert tensor to numpy and save as a WAV file
     audio_path = "/tmp/generated_audio.wav"
-    generated_audio.squeeze().cpu().numpy().tofile(audio_path)
+    audio_data = generated_audio[0].cpu().numpy()  # Access the first sample
+
+    # Save the generated audio
+    sf.write(audio_path, audio_data, 16000)  # Assuming a sample rate of 16kHz
 
     return audio_path
 
@@ -32,3 +36,4 @@ iface = gr.Interface(
 )
 
 iface.launch()
+