Spaces:
Running
Running
| import gradio as gr | |
| from transformers import pipeline | |
| # Load model from Hugging Face | |
| model_name = "MarieAngeA13/Sentiment-Analysis-BERT" | |
| classifier = pipeline("sentiment-analysis", model=model_name) | |
| # Prediction function | |
| def predict_sentiment(text): | |
| if text.strip() == "": | |
| return "Please enter some text." | |
| result = classifier(text)[0] | |
| label = result["label"] | |
| score = result["score"] | |
| return f"Sentiment: {label} (Confidence: {score:.2f})" | |
| # Gradio UI | |
| iface = gr.Interface( | |
| fn=predict_sentiment, | |
| inputs=gr.Textbox(lines=5, placeholder="Enter your review here..."), | |
| outputs="text", | |
| title="Sentiment Analysis App", | |
| description="Enter a review to classify it as Positive or Negative using a Hugging Face model." | |
| ) | |
| # Launch app | |
| if __name__ == "__main__": | |
| iface.launch() |