First commit

app.py

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+import gradio as gr
+import re
+
+from transformers import pipeline
+
+model = "Narrativaai/fake-news-detection-spanish"
+classifier = pipeline("text-classification", model=model)
+
+
+def predict(header, text):
+        results = classifier(header + " [SEP] " + text)
+        return results[0]["label"], round(results[0]["score"], 5)
+
+
+gradio_ui = gr.Interface(
+    fn=predict,
+    title="Fake News Detector (Spanish)",
+    description="Enter some text and check if model detects bullying.",
+    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()

requirements.txt

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+torch
+transformers