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from transformers import AutoProcessor, MusicgenForConditionalGeneration
from IPython.display import Audio
import scipy
import torch
import streamlit as st
def mu_gen(prompt):
processor = AutoProcessor.from_pretrained("facebook/musicgen-small")
model = MusicgenForConditionalGeneration.from_pretrained("facebook/musicgen-small")
device = torch.device("cpu")
model.to(device)
inputs = processor(
text = [str(prompt)], # This line is correct
padding=True,
return_tensors="pt",
)
inputs = {key: value.to(device) for key, value in inputs.items()}
# Generate audio on CPU
audio_values = model.generate(**inputs, max_new_tokens=256)
sampling_rate = model.config.audio_encoder.sampling_rate
# Create an Audio object from the generated audio
result = Audio(audio_values[0].numpy(), rate=sampling_rate)
return result
def main():
st.title("Text to Music Generator")
# Input text prompt
prompt = st.text_input("Enter a text prompt", "")
if st.button("Generate Music"):
if prompt:
# Call the mu_gen function to generate music
generated_music = mu_gen(prompt)
# Display the generated audio
st.audio(generated_music, format="audio/wav")
else:
st.warning("Please enter a text prompt.")
if __name__ == "__main__":
main() |