Create app.py

app.py

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+import gradio as gr
+from transformers import MusicGenForConditionalGeneration, MusicGenProcessor
+import torch
+
+# Load the MusicGen model and processor
+model_name = "facebook/musicgen-small"
+model = MusicGenForConditionalGeneration.from_pretrained(model_name)
+processor = MusicGenProcessor.from_pretrained(model_name)
+
+# Define a function to generate audio from text
+def generate_audio(text):
+    # Tokenize the input text
+    inputs = processor(text, return_tensors="pt")
+
+    # Generate audio (samples)
+    with torch.no_grad():
+        generated_audio = model.generate_audio(**inputs)
+
+    # Save the generated audio
+    audio_path = "/tmp/generated_audio.wav"
+    generated_audio.squeeze().cpu().numpy().tofile(audio_path)
+
+    return audio_path
+
+# Set up the Gradio interface
+iface = gr.Interface(
+    fn=generate_audio, 
+    inputs=gr.Textbox(label="Enter Text"), 
+    outputs=gr.Audio(type="file", label="Generated Audio"),
+    title="Text-to-Audio Chatbot",
+    description="Enter a text prompt and get a music clip generated by the MusicGen model."
+)
+
+iface.launch()