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import gradio as gr
from transformers import pipeline
from presentation import main_title, examples
model = 'hackathon-pln-es/Detect-Acoso-Twitter-Es'
article = """
# UNL: Universidad Nacional de Loja
### Miembros del equipo
- Anderson Quizhpe
- Luis Negrón
- David Pacheco
- Bryan Requenes
- Paul Pasaca
"""
def classify(text):
cls= pipeline("text-classification", model=model)
return cls(text)[0]['label']
gr.Interface(fn=classify, inputs=[gr.inputs.Textbox(
lines=5,
label="Texto a analizar:",
placeholder="Introduce o elige un ejemplo de twit:",
optional=False,
)], outputs=[gr.outputs.Textbox(label="Predicción"),
], description=main_title,
examples=examples,
article=article,
theme="peach",
thumbnail="None",
css="https://cdn.jsdelivr.net/npm/bootstrap@3.3.7/dist/css/bootstrap.min.css").launch(debug=True)
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