Create app.py

app.py

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+from voicefixer import VoiceFixer
+import gradio as gr
+voicefixer = VoiceFixer()
+def inference(audio):
+    voicefixer.restore(input=audio.name, # input wav file path
+                    output="output.wav", # output wav file path
+                    cuda=False, # whether to use gpu acceleration
+                    mode = 1) # You can try out mode 0, 1 to find out the best result
+    return 'output.wav'
+
+inputs = gr.inputs.Audio(type="file" label="Input Audio")
+outputs =  gr.outputs.Audio(type="file",label="Output Audio")
+
+
+title = "VITS"
+description = "demo for VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech. To use it, simply add your text, or click one of the examples to load them. Read more at the links below."
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2106.06103'>Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech</a> | <a href='https://github.com/jaywalnut310/vits'>Github Repo</a></p>"
+
+
+
+gr.Interface(inference, inputs, outputs, title=title, description=description, article=article).launch()