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| import gradio as gr | |
| from transformers import pipeline | |
| # Load pre-trained sentiment-analysis pipeline | |
| model = pipeline("sentiment-analysis", model="distilbert-base-uncased") | |
| # Function to classify sentiment | |
| def analyze_sentiment(feedback_text): | |
| result = model(feedback_text) | |
| return result[0]['label'], result[0]['score'] # returns label and confidence score | |
| # Gradio interface | |
| iface = gr.Interface(fn=analyze_sentiment, | |
| inputs="text", | |
| outputs=["text", "number"]) | |
| iface.launch() | |