| import gradio as gr | |
| from transformers import pipeline | |
| pipe = pipeline(task="text-classification", model="hoangthan/bert-vi-sms-classification") | |
| def classify_audio(filepath): | |
| preds = pipe(filepath) | |
| outputs = {} | |
| for p in preds: | |
| outputs[p["label"]] = p["score"] | |
| return outputs | |
| gradio_app = gr.Interface( | |
| fn=classify_audio, inputs=gr.Textbox(), outputs=gr.Label() | |
| ) | |
| if __name__ == "__main__": | |
| gradio_app.launch(debug=True) |