| import gradio as gr | |
| from transformers import pipeline | |
| model = pipeline("sentiment-analysis", model="nlptown/bert-base-multilingual-uncased-sentiment") | |
| def sentiment(text): | |
| analysis = model(text) | |
| return analysis[0]['label'] | |
| with gr.Blocks() as app: | |
| gr.Markdown("# Sentiment Analysis") | |
| text_input = gr.Textbox(label="Enter a sentence or paragraph:", lines=10) | |
| analyze_button = gr.Button("Analyze Sentiment") | |
| output_text = gr.Textbox(label="Predicted Sentiment (1 to 5 stars):", interactive=False) | |
| analyze_button.click(sentiment, inputs=text_input, outputs=output_text) | |
| examples = [ | |
| "I love this product! It's amazing!", | |
| "This was the worst experience I've ever had." | |
| ] | |
| gr.Examples( | |
| examples=examples, | |
| inputs=text_input, | |
| label="Try these examples" | |
| ) | |
| app.launch() | |