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import gradio as gr | |
import re | |
from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline | |
ckpt = "Narrativaai/fake-news-detection-spanish" | |
tokenizer = AutoTokenizer.from_pretrained(ckpt) | |
model = AutoModelForSequenceClassification.from_pretrained(ckpt) | |
classifier = pipeline("text-classification", model=model, tokenizer=tokenizer) | |
def prediction(header, text): | |
results = classifier(header + " [SEP] " + text) | |
return results[0]["label"], round(results[0]["score"], 5) | |
gradio_ui = gr.Interface( | |
fn=prediction, | |
title="Fake News Detector (Spanish)", | |
description="Enter some text and check if it is Real or Fake", | |
inputs=[ | |
gr.inputs.Textbox(lines=1, label="Type/Paste your headline here"), | |
gr.inputs.Textbox(lines=6, label="Type/Paste the article body here"), | |
], | |
outputs=[ | |
gr.outputs.Textbox(label="Label"), | |
gr.outputs.Textbox(label="Score"), | |
], | |
examples=[ | |
], | |
) | |
gradio_ui.launch() |