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app.py

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+from fastai.text.all import *
+import gradio as gr
+
+
+# Cargamos el learner
+learn = load_learner('export.pkl')
+
+
+# Definimos una función que se encarga de llevar a cabo las predicciones
+def predict(text):
+    pred = learn.predict(text)
+    return pred
+
+# Establecemos el título de la App y también indicamos 
+title = "Fake-News Detector - Language Models"
+description = "A Fake-News detector trained on HuggingFace LIAR dataset with fastai. It classifies news in 6 categories ranging from 0 to 5: [0]- False, [1]-Half-True, [2]-Mostly-True, [3]-True, [4]-Barely-True, and [5]-Pants-Fire"
+            
+texto1 = "Iran President Hassan Rouhani has more Cabinet members with Ph.D.s from American universities than members of Barack Obamas Cabinet."
+
+texto2 = "Says At age 76 when you most need it, you are not eligible for cancer treatment under Affordable Care Act."
+
+texto3 = "More than 250 (voter registration) groups, ranging across the entire political spectrum, have filed with the state and are registering voters right now."
+    
+# Creamos la interfaz y la lanzamos. 
+gr.Interface(fn=predict, inputs="text", outputs="text", title=title, description=description, examples=[texto1,texto2, texto3]).launch(share=False)
+