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| import gradio as gr | |
| from setfit import SetFitModel | |
| try: | |
| transactional_model = SetFitModel.from_pretrained("edugargar/risk_model") | |
| except Exception as e: | |
| raise RuntimeError("Failed to load model: " + str(e)) | |
| def predict_and_score(text): | |
| preds = transactional_model([text]) | |
| predicted_class = preds[0] | |
| probs = transactional_model.predict_proba([text]) | |
| probability_distribution = probs[0] | |
| probability_str = ", ".join(f"{p:.4f}" for p in probability_distribution) | |
| return predicted_class, probability_str | |
| with gr.Blocks() as demo: | |
| gr.Markdown("## Risk Model Prediction") | |
| text_input = gr.Textbox(label="Enter your text here:") | |
| predict_button = gr.Button("Predict") | |
| prediction_output = gr.Textbox(label="Predicted Class:") | |
| score_output = gr.Textbox(label="Score (Probability Distribution):") | |
| predict_button.click(fn=predict_and_score, | |
| inputs=[text_input], | |
| outputs=[prediction_output, score_output]) | |
| demo.launch() |