The app

app.py

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+import gradio as gr
+from transformers import pipeline
+
+def fill_mask(stmt,model):
+    if model == 'bert':
+        debiased = 'Daniel-Saeedi/debiased-bert-base-uncased'
+        original = 'bert-base-uncased'
+
+    
+    unmasker_1 = pipeline('fill-mask', model=debiased)
+    
+    unmasker_2 = pipeline('fill-mask', model=original)
+    
+    return unmasker_1(stmt), unmasker_2(stmt)
+
+
+demo = gr.Interface(
+        fill_mask,
+        inputs = [
+        gr.Textbox(placeholder="Fill Mask"),
+        gr.Radio(choices=['bert'],value='bert')
+        ],
+        outputs = [gr.Textbox(label="Debiased:"),gr.Textbox(label="Original"), gr.Markdown(
+            value="<h3>How the difference is measured?</h3> <p>abs(similarity(gendered_word1,occupation)-similarity(gendered_word2,occupation))</p>")],
+            description = '<a href="https://aclanthology.org/2020.acl-main.484/">Double-Hard Debias: Tailoring Word Embeddings for Gender Bias Mitigation</a>'
+    )
+if __name__ == '__main__':
+    demo.launch()

requirements.txt

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+numpy
+transformer