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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) |