File size: 1,179 Bytes
784b06e 226a57a 784b06e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 |
# -*- coding: utf-8 -*-
"""
Created on Mon Aug 25 14:10:33 2025
@author: shuangshuang
"""
from transformers import pipeline
import gradio as gr
# Load model
classifier = pipeline(
"sentiment-analysis",
model="nlptown/bert-base-multilingual-uncased-sentiment",
# device=-1,
)
# Map labels
label_map = {
"1 star": "very bad",
"2 stars": "bad",
"3 stars": "neutral",
"4 stars": "good",
"5 stars": "very good",
}
# Prediction function
def predict(text):
text = text.strip()
if not text:
return "Please enter some text."
result = classifier(text)[0]
label = result["label"]
score = result["score"]
mapped = label_map[label]
return f"Prediction: {mapped}\nConfidence: {score:.2f}"
# Gradio interface
interface = gr.Interface(
fn=predict,
inputs=gr.Textbox(lines=2, placeholder="Enter a sentence..."),
outputs="text",
title="Sentiment Analysis",
description="Enter a sentence to analyze its sentiment.",
examples=["I love this product!", "This is terrible."],
)
# Launch (Hugging Face Spaces doesn't need special params)
if __name__ == "__main__":
interface.launch(ssr_mode=False)
|