| import gradio as gr | |
| from transformers import pipeline | |
| # Load a sentiment analysis pipeline from Hugging Face | |
| sentiment_pipeline = pipeline(task="text-classification", model="SamLowe/roberta-base-go_emotions", top_k=None) | |
| def analyze_sentiment(text): | |
| result = sentiment_pipeline(text) | |
| print(result) | |
| return result[0][0]["label"] #pipeline return an aray of array of dictionary | |
| # Create a Gradio interface | |
| iface = gr.Interface( | |
| fn=analyze_sentiment, | |
| inputs=[gr.Textbox(label="Enter text here")], | |
| outputs=[gr.Label(label="Sentiment")], | |
| title="Sentiment Analyzer", | |
| description="Enter a text to analyze its sentiment", | |
| ) | |
| # Launch the Gradio interface | |
| iface.launch() |