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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")
# Input text prompt
title = st.text_input('Write a prompt (จะใช้เวลาค่อนข้างมากในการสร้างเนื่องจากใช้ CPU ในการรันโมเดล)', "")
if st.button('Generate Image'):
# Call the pic_mo function to generate an image
generated_music = mu_gen(prompt)
# Display the generated image
st.image(generated_music, caption='Generated Music', use_column_width=True)
if __name__ == '__main__':
main() |