import gradio as gr | |
from transformers import pipeline | |
# Cargar el modelo de Hugging Face para an谩lisis de emociones | |
classifier = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-large") | |
# Funci贸n para predecir la emoci贸n | |
def detect_emotion(text): | |
result = classifier(text) | |
emotion = result[0]['label'] | |
return emotion | |
# Crear la interfaz con Gradio | |
interface = gr.Interface( | |
fn=detect_emotion, | |
inputs="text", | |
outputs="text", | |
live=True, | |
title="Detector de Emociones", | |
description="Introduce un texto para detectar la emoci贸n que expresa." | |
) | |
# Lanzar la interfaz | |
interface.launch() | |