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| from transformers import pipeline | |
| import gradio as gr | |
| classifier = pipeline("sentiment-analysis") | |
| def analyze_sentiment(text): | |
| if not text: | |
| return "No input", 0 | |
| try: | |
| result = classifier(text)[0] # should return a dict | |
| label = result.get('label', 'Unknown') | |
| score = round(result.get('score', 0), 3) | |
| return label, score | |
| except Exception as e: | |
| return f"Error: {str(e)}", 0 | |
| iface = gr.Interface( | |
| fn=analyze_sentiment, | |
| inputs=gr.Textbox(lines=2, placeholder="Enter text here..."), | |
| outputs=[ | |
| gr.Textbox(label="Sentiment"), | |
| gr.Number(label="Confidence Score") | |
| ], | |
| title="Sentiment Analyzer", | |
| description="Enter a sentence to get its sentiment (POSITIVE/NEGATIVE) and confidence score." | |
| ) | |
| iface.launch() | |