Create app.py

app.py

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+import gradio as gr
+import torchaudio
+import torch
+from transformers import AutoProcessor, MusicgenForConditionalGeneration
+
+# Load MusicGen model
+model_name = "facebook/musicgen-small"
+model = MusicgenForConditionalGeneration.from_pretrained(model_name)
+processor = AutoProcessor.from_pretrained(model_name)
+model.to("cuda" if torch.cuda.is_available() else "cpu")
+
+def generate_music(description):
+    inputs = processor(text=[description], return_tensors="pt")
+    inputs = {k: v.to(model.device) for k, v in inputs.items()}
+    audio_values = model.generate(**inputs, max_new_tokens=256)
+    audio = processor.decode(audio_values[0], sampling_rate=16000)
+    torchaudio.save("output.wav", audio.unsqueeze(0), 16000)
+    return "output.wav"
+
+# Gradio UI
+demo = gr.Interface(
+    fn=generate_music,
+    inputs=gr.Textbox(label="Describe your song"),
+    outputs=gr.Audio(label="Generated Track"),
+    title="LarynxLab MVP",
+    description="Type a music idea and get a short AI instrumental."
+)
+
+demo.launch()