Update app.py

app.py

@@ -1,61 +1,18 @@
-!pip install -q -U diffusers transformers accelerate
-     
-
-from diffusers import AudioLDM2Pipeline
-     
-
-import torch
-model_id = "cvssp/audioldm2"
-
-pipe = AudioLDM2Pipeline.from_pretrained(
-    model_id,
-    torch_dtype = torch.float16,
-).to("cuda")
-     
-
-
-prompt = "A cheerful ukulele strumming in a beachside jam."
-     
-
-generator = torch.Generator("cuda").manual_seed(0)
-     
+import gradio as gr
+from transformers import pipeline
 
-audio = pipe(
-    prompt,
-    audio_length_in_s = 10.24,
-    generator = generator,
-).audios[0]
-     
+tts = pipeline("text-to-audio", model="facebook/musicgen-small")
 
-audio = pipe(
-    prompt,
-    negative_prompt = negative_prompt,
-    audio_length_in_s = 10.24,
-    generator = generator,
-).audios[0]
-     
-from IPython.display import Audio
-Audio(audio, rate = 16000)
-     
-!pip install -q gradio
-import gradio as gr
-     
+def text_to_audio(text):
+    output = tts(text)
+    return output["audio"]
+iface = gr.Interface(
+    fn=text_to_audio,
+    inputs=gr.Textbox(label="Text"),
+    outputs=gr.Audio(label="Audio"),
+    title="Text-to-Audio",
 
-def create_music(prompt):
-  negative_prompt = "Low quality"
-  audio = pipe(
-    prompt,
-    negative_prompt = negative_prompt,
-    audio_length_in_s = 10.24,
-    generator = generator,
-  ).audios[0]
-  return 16000, audio
-     
+)
 
-interface = gr.Interface(
-    title = "Music Generation App",
-    examples = ["A cheerful ukulele strumming in a beachside jam."],
-    fn = create_music,
-    inputs = gr.Textbox(),
-    outputs = "audio",
-).launch(debug=True, share=True)
+if __name__ == "__main__":
+    iface.launch()