app.py

import gradio as gr
title = "Medical Entity Mask Language Modeling (MLM)"
description = "Medical Entity Feature Extraction uses Match Language Modeling to fill in the blank with likely word classification based on context."
article = "<p style='text-align: center'></p>"
examples = [
    ["Scientific breakthroughs in treatment of HIV/AIDS may be solved in our lifetime using a procedure called [MASK] modulation which strengthens the immune system to fight the disease."],["A disease called [MASK] disease involves progressive memory loss and has new treatments to improve memory and delay progression of the disease."],["[MASK] refers to the uncontrolled growth of abnormal cells in the body.  With chemotherapy and radiation therapy have improvements and replacements that destroy cancer cells before they become resistant to current treatment methods."],["The hereditary disease [MASK] is caused by mucus abnormally thick preventing lungs and pancreas from doing their jobs correctly."],["[MASK] or atherosclerosis is the buildup of cholesterol, fatty cells, and inflammatory deposits in the arteries.  Stem cells, mechanical devices, and lowering cholesterol and blood pressure levels are helping prevention."]
]

gr.Interface.load("huggingface/ajitrajasekharan/biomedical",title=title,description=description,article=article, examples=examples, allow_flagging="never",enable_queue=True).launch()