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import gradio as gr | |
from transformers import pipeline | |
# 1) Initialize zero-shot classifier | |
classifier = pipeline( | |
task="zero-shot-classification", | |
model="facebook/bart-large-mnli" | |
) | |
# 2) Define candidate labels | |
LABELS = ["linear algebra", "calculus", "probability", "geometry"] | |
# 3) Gradio interface function | |
def tag_question(question): | |
result = classifier(question, candidate_labels=LABELS) | |
return {lbl: round(score, 3) for lbl, score in zip(result["labels"], result["scores"])} | |
# 4) Build UI | |
iface = gr.Interface( | |
fn=tag_question, | |
inputs=gr.Textbox(lines=3, placeholder="Enter your MCQ here..."), | |
outputs=gr.Label(num_top_classes=3), | |
title="Zero-Shot Question Tagger", | |
description="Classify questions into math topics without any training data." | |
) | |
if __name__ == "__main__": | |
iface.launch() | |