Update app.py

app.py

@@ -1,24 +1,12 @@
 import gradio as gr
-import scipy
-from transformers import pipeline
-from transformers import AutoProcessor, MusicgenForConditionalGeneration
+from diffusers import DiffusionPipeline
 
-processor = AutoProcessor.from_pretrained("facebook/musicgen-small")
-model = MusicgenForConditionalGeneration.from_pretrained("facebook/musicgen-small")
+model_name = "facebook/musicgen-small"  
+pipe = DiffusionPipeline.from_pretrained(model_name)
 
+def generate(prompt):
+    return audio = pipe(prompt)
 
-
-def generate(description):
-    audio = processor(text=description, padding=True, return_tensors="pt")
-    audio_values = model.generate(**audio, max_new_tokens=256)
-    sampling_rate = model.config.audio_encoder.sampling_rate
-    return scipy.io.wavfile.write("musicgen_out.wav", rate=sampling_rate, data=audio_values[0, 0].numpy())
-
-demo = gr.Interface(
-    fn=generate,
-    inputs=gr.Textbox(label="Enter Text to Convert to Audio"),
-    outputs=gr.Audio(label="Generated Audio"),
-    live=True
-)
+demo = gr.Interface(fn = generate, inputs="text", outputs=audio.save("output_music.wav"))
 
 demo.launch()