| import gradio as gr | |
| from transformers import pipeline | |
| sentiment_analyzer = pipeline("sentiment-analysis", model="nlptown/bert-base-multilingual-uncased-sentiment") | |
| def analyze_sentiment(text): | |
| result = sentiment_analyzer(text)[0] | |
| score = result['label'] | |
| return score | |
| interface = gr.Interface( | |
| fn=analyze_sentiment, | |
| inputs=[ | |
| gr.Textbox(label="Enter your text here", placeholder="Type a sentence or paragraph...", lines=5), | |
| ], | |
| outputs=gr.Label(label="Predicted Sentiment (1-5 stars)"), | |
| examples=[ | |
| ["I love this product! It's amazing!"], | |
| ["This was the worst experience I've ever had."], | |
| ["The movie was okay, not great but not bad either."], | |
| ["Absolutely fantastic! I would recommend it to everyone."], | |
| ["I'm very disappointed with the customer service."], | |
| ["The concert was fantastic, I had an amazing time!"], | |
| ["I regret buying this product, it's terrible."] | |
| ], | |
| title="Sentiment Analysis App", | |
| description="This app analyzes the sentiment of the text you provide, showing a score from 1 to 5 stars, where 1 is negative and 5 is positive." | |
| ) | |
| interface.launch() | |