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import gradio as gr | |
from transformers import pipeline | |
# Load pre-trained sentiment analysis model from Hugging Face | |
sentiment_pipeline = pipeline("tabularisai/multilingual-sentiment-analysis") | |
def analyze_sentiment(text): | |
result = sentiment_pipeline(text)[0] | |
label = result['label'] | |
score = round(result['score'], 3) | |
return f"Sentiment: {label} | Confidence: {score}" | |
# Gradio UI | |
iface = gr.Interface( | |
fn=analyze_sentiment, | |
inputs=gr.Textbox(label="Enter Text"), | |
outputs=gr.Textbox(label="Sentiment Result"), | |
title="Sentiment Analysis with Hugging Face π€", | |
description="This app performs sentiment analysis on user input text using Hugging Face Transformers." | |
) | |
if __name__ == "__main__": | |
iface.launch() | |