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Running
on
T4
Running
on
T4
import gradio as gr | |
from spectro import wav_bytes_from_spectrogram_image | |
from diffusers import StableDiffusionPipeline | |
model_id = "riffusion/riffusion-model-v1" | |
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16) | |
pipe = pipe.to("cuda") | |
def predict(prompt): | |
spec = pipe(prompt).images[0] | |
wav = wav_bytes_from_spectrogram_image(spec) | |
with open("output.wav", "wb") as f: | |
f.write(wav[0].getbuffer()) | |
return 'output.wav' | |
gr.Interface( | |
predict, | |
inputs="text", | |
outputs=gr.outputs.Audio(type='filepath'), | |
title="Riffusion", | |
).launch(share=True, debug=True) | |