import gradio as gr from transformers import pipeline # Load your sentiment classification model pipe = pipeline("text-classification", model="sharmax-vikas/IMDB_Sentiment") # Label mapping for the model label_map = { "LABEL_0": "Negative", "LABEL_1": "Positive" } # Define the function used by Gradio def respond(message, history, *args): result = pipe(message)[0] label = label_map.get(result["label"], result["label"]) # Map label score = round(result["score"]*100, 2) return f"Prediction: {label} (Confidence: {score})" # Create a simple Gradio ChatInterface with your model demo = gr.ChatInterface( fn=respond, additional_inputs=[], title="IMDB Sentiment Classifier" ) if __name__ == "__main__": demo.launch(share=True)