Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+classifier = pipeline(task="text-classification", model="christinacdl/XLM_RoBERTa-Clickbait-Detection-new")
+
+def text_classification(text):
+    result= classifier(text)
+    label = result[0]['label']
+    score = result[0]['score']
+    formatted_output = f"The label is {label} with the probability {score*100:.2f}%"
+    return formatted_output
+
+examples=["Your Old Passport Will Be Replaced With Smart E-passport, Here Is Everything You Need To Know", "17 Things That Are Too Real For People Who Always Drop Their Phone"]
+
+gradio_app = gr.Interface(fn=text_classification, 
+                         inputs= gr.Textbox(lines=2, label="Text", placeholder="Enter text here..."), 
+                         outputs=gr.Textbox(lines=2, label="Text Classification Result"),
+                         title="Is it clickbait?",
+                         description="Enter a text to check if it is clickbait or not!",
+                         examples=examples)
+
+
+if __name__ == "__main__":
+    gradio_app.launch()