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fbd3042 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | import gradio as gr
from transformers import pipeline
clf = pipeline("text-classification", model="your-username/bert-base-uncased-yelp")
def predict(text):
pred = clf(text)[0]
return f"Label: {pred['label']} (score={pred['score']:.2f})"
demo = gr.Interface(
fn=predict,
inputs=gr.Textbox(lines=4, placeholder="Paste a customer review here..."),
outputs="text",
title="Sentiment Analysis Demo",
description="Fine‑tuned BERT‑base model on Yelp Polarity dataset"
)
if __name__ == "__main__":
demo.launch()
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