| from transformers import pipeline | |
| import gradio as gr | |
| # Load pretrained sentiment analysis model | |
| classifier = pipeline("sentiment-analysis") | |
| # Prediction function | |
| def analyze_sentiment(text): | |
| result = classifier(text) | |
| label = result[0]['label'] | |
| score = result[0]['score'] | |
| return f"Sentiment: {label}\nConfidence: {score:.2f}" | |
| # Create Gradio interface | |
| interface = gr.Interface( | |
| fn=analyze_sentiment, | |
| inputs=gr.Textbox(lines=3, placeholder="Enter text here..."), | |
| outputs="text", | |
| title="Sentiment Analysis App", | |
| description="AI model deployed using Hugging Face Spaces" | |
| ) | |
| # Launch app | |
| interface.launch() |