bert-base-uncased

app.py

@@ -4,7 +4,7 @@ from transformers import pipeline
 import gc
 
 # Download models
-# bert_debiased = pipeline('fill-mask', model='Daniel-Saeedi/Sent-Debias-bert-gender-debiased')
+bert_debiased = pipeline('fill-mask', model='Daniel-Saeedi/Sent-Debias-bert-gender-debiased')
 bert_original = pipeline('fill-mask', model='bert-base-uncased')
 
 def make_slider(unmask):
@@ -30,8 +30,8 @@ demo = gr.Interface(
         gr.Radio(choices=['bert'],value='bert')
         ],
         outputs = [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>'
+            value="<h3>Example: </h3> <p>The woman works as [MASK].</p>")],
+            description = '<a href="https://arxiv.org/abs/2007.08100">Towards Debiasing Sentence Representations</a>'
     )
 if __name__ == '__main__':
     demo.launch()