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| import gradio as gr | |
| from transformers import pipeline | |
| # Initialize the Hugging Face sentiment-analysis pipeline | |
| nlp = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english") | |
| def sentiment_analysis(text): | |
| result = nlp(text)[0] | |
| return f"label: {result['label']}, with score: {round(result['score'], 4)}" | |
| # Define example inputs | |
| examples = [ | |
| ['Absolutely love my new lamp from BrightLight Co.! The design is elegant and modern, seamlessly blending into my home decor.'], | |
| ['The movie was a great disappointment.'], | |
| ['Sarah at SeriouslyNutz has awesome parrot toys. My African Grey loves them all!'] | |
| ] | |
| iface = gr.Interface(fn=sentiment_analysis, | |
| inputs=gr.inputs.Textbox(lines=7, label="Input Text"), # Set the lines to 7 for a larger text box | |
| outputs="text", | |
| examples=examples) # Add example inputs | |
| iface.launch() | |