| import gradio as gr | |
| from transformers import pipeline | |
| classifier = pipeline("text-classification", model="SamLowe/roberta-base-go_emotions") | |
| def predict(text): | |
| result = classifier(text) | |
| print(f"{result}") | |
| return result | |
| demo = gr.Interface( | |
| fn = predict, | |
| inputs = 'text', | |
| outputs = 'text', | |
| ) | |
| # demo = gr.Interface.from_pipeline(classifier) | |
| demo.launch() |