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import os | |
import numpy as np | |
import gradio as gr | |
# Use a pipeline as a high-level helper | |
import requests | |
API_URL = "https://api-inference.huggingface.co/models/asg2024/vits-ar-sa" | |
def query(text): | |
payload={"inputs": text} | |
response = requests.post(API_URL, json=payload) | |
return response.content | |
def reverse_audio(text): | |
data = query(text) | |
return data#(16000, np.flipud(data)) | |
demo = gr.Interface( | |
fn=reverse_audio, | |
inputs="text", | |
outputs="audio" | |
) | |
if __name__ == "__main__": | |
demo.launch() |