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| import gradio as gr | |
| from transformers import pipeline | |
| # Load the pre-trained pipeline for sentiment analysis | |
| sentiment_analysis = pipeline('text-classification', model='distilbert-base-uncased-finetuned-sst-2-english') | |
| # Define the function that will be called by Gradio | |
| def analyze_sentiment(input_text): | |
| output = sentiment_analysis(input_text) | |
| sentiment = output[0]['label'] | |
| score = output[0]['score'] | |
| return f"Sentiment: {sentiment} (Score: {score:.2f})" | |
| # Create the Gradio interface | |
| gr.Interface(fn=analyze_sentiment, inputs="text", outputs="text", title="Sentiment Analysis AI").launch() |