| import gradio as gr | |
| from datasets import load_dataset | |
| from transformers import pipeline | |
| from presentation import main_title, examples | |
| model_name= 'hackathon-pln-es/electricidad-small-discriminator-finetuned-clasificacion-comentarios-suicidas' | |
| def clasificar_comentarios(comentario): | |
| cls= pipeline("text-classification", model=model_name) | |
| return cls(comentario)[0]['label'] | |
| if __name__ == "__main__": | |
| gr.Interface( | |
| fn=clasificar_comentarios, | |
| inputs=[ | |
| gr.inputs.Textbox( | |
| lines=10, | |
| label="Comentario a analizar:", | |
| placeholder="Ingrese el comentario por favor...", | |
| optional=False, | |
| ), | |
| ], | |
| outputs=[ | |
| gr.outputs.HTML( | |
| label="Resultado:" | |
| ) | |
| ], | |
| description=main_title, | |
| examples=examples, | |
| theme="seafoam", | |
| thumbnail="None", | |
| css="https://cdn.jsdelivr.net/npm/bootstrap@3.3.7/dist/css/bootstrap.min.css", | |
| ).launch() |