| import gradio as gr | |
| from transformers import pipeline | |
| pipeline = pipeline(task="text-classification", model="distilbert-base-uncased-finetuned-sst-2-english") | |
| def predict(text): | |
| predictions = pipeline(text) | |
| return {p["label"]: p["score"] for p in predictions} | |
| gr.Interface( | |
| predict, | |
| inputs="text", | |
| outputs=gr.outputs.Label(num_top_classes=5), | |
| title="Text Classification", | |
| ).launch() |