| import gradio as gr | |
| from transformers import pipeline | |
| from presentation import main_title, examples | |
| model = 'hackathon-pln-es/Detect-Acoso-Twitter-Es' | |
| def classify(text): | |
| cls= pipeline("text-classification", model=model) | |
| return cls(text)[0]['label'] | |
| gr.Interface(fn=classify, inputs=["textbox"], outputs="text", description=main_title, | |
| examples=examples, | |
| theme="peach", | |
| thumbnail="None", | |
| css="https://cdn.jsdelivr.net/npm/bootstrap@3.3.7/dist/css/bootstrap.min.css").launch(debug=True) | |