Update app.py

app.py

@@ -19,8 +19,8 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 torch_dtype = torch.float16 if device == "cuda" else torch.float32
 
 # Load the StableAudio model from Hugging Face Hub
-#pipe = StableAudioPipeline.from_pretrained("stabilityai/stable-audio-open-1.0", torch_dtype=torch_dtype)
-#pipe = pipe.to(device)
+pipe = StableAudioPipeline.from_pretrained("stabilityai/stable-audio-open-1.0", torch_dtype=torch_dtype)
+pipe = pipe.to(device)
 
 # Initialize Flask app
 app = Flask(__name__)
@@ -39,8 +39,8 @@ def generate_audio():
     try:
         
         # Load the StableAudio model from Hugging Face Hub
-        pipe = StableAudioPipeline.from_pretrained("stabilityai/stable-audio-open-1.0", torch_dtype=torch_dtype)
-        pipe = pipe.to(device)
+        #pipe = StableAudioPipeline.from_pretrained("stabilityai/stable-audio-open-1.0", torch_dtype=torch_dtype)
+        #pipe = pipe.to(device)
         
         # Generate the audio using StableAudioPipeline
         generator = torch.Generator(device)
@@ -61,7 +61,6 @@ def generate_audio():
         output_io.truncate(0) # Clears any residual data from previous calls
         output_audio = audio_output[0].T.float().cpu().numpy()
         sf.write(output_io, output_audio, pipe.vae.sampling_rate, format="WAV")  # Save as WAV or your preferred format
-        #output_io.truncate(0)  # Clears the buffer's content
         output_io.seek(0)  # Reset buffer pointer to beginning
 
         # Send the file in response as attachment for download