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import gradio as gr
import re
from transformers import pipeline
sp_model = "JonatanGk/roberta-base-bne-finetuned-catalonia-independence-detector"
ca_model = "JonatanGk/roberta-base-ca-finetuned-catalonia-independence-detector"
sp_analysis = pipeline("text-classification", model=sp_model, tokenizer=sp_model)
ca_analysis = pipeline("text-classification", model=ca_model, tokenizer=ca_model)
def bullying_analysis(language, text):
if language == 'Spanish':
results = sp_analysis(text)
elif language == 'Catalan':
results = ca_analysis(text)
return results[0]["label"], round(results[0]["score"], 5)
gradio_ui = gr.Interface(
fn=bullying_analysis,
title="Catalonia independence detector (Spanish/Catalan)",
description="Enter some text and check if model detects is favor/neutral/against Catalonia independence.",
inputs=[
gr.inputs.Radio(['Spanish','Catalan'],label='Language',),
gr.inputs.Textbox(lines=5, label="Paste some text here"),
],
outputs=[
gr.outputs.Textbox(label="Label"),
gr.outputs.Textbox(label="Score"),
],
examples=[
['Spanish', "Junqueras, sobre la decisi贸n judicial sobre Puigdemont: La justicia que falta en el Estado llega y llegar谩 de Europa"],
['Spanish', "Desconvocada la manifestaci贸n del domingo en Barcelona en apoyo a Puigdemont"],
['Catalan', "Puigdemont, a l'estat espanyol: Quatre anys despr茅s, ens hem guanyat el dret a dir prou"],
['Catalan', "Llarena demana la detenci贸 de Com铆n i Ponsat铆 aprofitant que s贸n a It脿lia amb Puigdemont"],
],
)
gradio_ui.launch() |