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import gradio as gr | |
import scipy | |
from diffusers import DiffusionPipeline | |
model_id = "harmonai/maestro-150k" | |
pipeline = DiffusionPipeline.from_pretrained(model_id) | |
pipeline = pipeline.to("cuda") | |
def denoise(length_sec): | |
audios = pipeline(audio_length_in_s=length_sec).audios | |
for audio in audios: | |
scipy.io.wavfile.write("maestro_test.wav", pipe.unet.sample_rate, audio.transpose()) | |
return "maestro_test.wav" | |
gr.Interface(fn=denoise, inputs=gr.Slider(1.0, 6.0, value=3.0, step=0.5, label="Audio length in seconds"), outputs="audio").launch() |