| import gradio as gr | |
| from transformers import pipeline | |
| # Load the model using pipeline | |
| pipe = pipeline("audio-classification", model="MelodyMachine/Deepfake-audio-detection-V2") | |
| # Define the prediction function | |
| def predict(audio): | |
| return pipe(audio) | |
| # Create the Gradio interface | |
| iface = gr.Interface( | |
| fn=predict, | |
| inputs=gr.Audio(source="microphone", type="filepath"), | |
| outputs="label", | |
| title="Deepfake Audio Detection", | |
| description="Upload an audio file or record your voice to detect if the audio is a deepfake." | |
| ) | |
| # Launch the interface | |
| iface.launch() | |