Spaces:
Running
Running
from transformers import pipeline | |
import gradio as gr | |
summarizer = pipeline("summarization", model="josmunpen/mt5-small-spanish-summarization") | |
def generate_summary(text): | |
summary = summarizer(text, max_length=100, min_length=30, do_sample=False) | |
return summary[0]['summary_text'] | |
with gr.Blocks() as demo: | |
gr.Markdown(""" | |
# Resumen de Texto en Español | |
Esta aplicación permite generar resúmenes breves de textos largos en español. | |
Solo necesitas introducir el texto y el modelo generará un resumen conciso. | |
""") | |
gr.Interface( | |
fn=generate_summary, | |
inputs=gr.Textbox(label="Introduce el texto largo", placeholder="Escribe o pega un texto aquí..."), | |
outputs=gr.Textbox(label="Resumen"), | |
) | |
gr.Markdown(""" | |
--- | |
Demostración de resumen de texto usando el modelo [josmunpen/mt5-small-spanish-summarization](https://huggingface.co/josmunpen/mt5-small-spanish-summarization). | |
Desarrollado con ❤️ por [@srjosueaaron](https://www.instagram.com/srjosueaaron/). | |
""") | |
if __name__ == "__main__": | |
demo.launch() | |