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| import gradio as gr | |
| import joblib | |
| # Load model + vectorizer | |
| model = joblib.load("model.pkl") | |
| vectorizer = joblib.load("vectorizer.pkl") | |
| #import skops.io as sio | |
| #model = sio.load("model.skops") | |
| #vectorizer = sio.load("vectorizer.skops") | |
| def predict_category(text): | |
| X_emb = vectorizer.transform([text]) | |
| pred = model.predict(X_emb)[0] | |
| return pred | |
| demo = gr.Interface( | |
| fn=predict_category, | |
| inputs=gr.Textbox(lines=2, placeholder="Enter a headline..."), | |
| outputs="text", | |
| title="📰 News Headline Classifier", | |
| description="Type a news headline and get its predicted category." | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() |