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| import gradio as gr | |
| from transformers import pipeline | |
| # Load the classification pipeline from your model on the hub | |
| classifier = pipeline("text-classification", model="PrimeQA/tydiqa-boolean-question-classifier") | |
| def classify_text(text): | |
| results = classifier(text) | |
| # Format output nicely | |
| return {res["label"]: round(res["score"], 4) for res in results} | |
| # Build Gradio UI | |
| gr.Interface( | |
| fn=classify_text, | |
| inputs=gr.Textbox(lines=3, placeholder="Enter your text here..."), | |
| outputs="label", | |
| title="Boolean Classifier", | |
| description="A classification model by Mahmoud3899" | |
| ).launch() |