demo-class / app.py
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import gradio as gr
from transformers import pipeline
# Load the pre-trained sentiment analysis model
sentiment_analysis = pipeline(model="siebert/sentiment-roberta-large-english")
# Define the function for sentiment prediction
def predict_sentiment(text):
result = sentiment_analysis(text)
return result[0]['label']
# Create the Gradio interface
iface = gr.Interface(fn=predict_sentiment, inputs="text", outputs="text",
title="Sentiment Analyser",
description="Here's a demo SA.",)
# Launch the app
iface.launch(share=True)