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import base64 |
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import streamlit as st |
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def get_base64(file_path): |
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with open(file_path, "rb") as file: |
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base64_bytes = base64.b64encode(file.read()) |
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base64_string = base64_bytes.decode("utf-8") |
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return base64_string |
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def set_background(png_file): |
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bin_str = get_base64(png_file) |
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page_bg_img = ( |
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""" |
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<style> |
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.stApp { |
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background-image: url("data:image/png;base64,%s"); |
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background-size: auto; |
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} |
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</style> |
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""" |
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% bin_str |
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) |
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st.markdown(page_bg_img, unsafe_allow_html=True) |
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set_background("tg_toxic.png") |
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title_html = """<p style='font-size: 50px; color: black;'>Toxicity Assessment of User Comments</p>""" |
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st.markdown(title_html, unsafe_allow_html=True) |
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st.write( |
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"""<p style='font-size: 18px; color: black;'>Used model: rubert-tiny-toxicity</p> |
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<p style='font-size: 18px; color: black;'>Accuracy:</p> |
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<p style='font-size: 18px; color: black;'>Pretrained model: 82%</p> |
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<p style='font-size: 18px; color: black;'>After training on user's data: 90%</p> |
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<a href='https://t.me/toxicity_assessment12345_bot' style='font-size: 18px; color: black; text-decoration: underline;'>Link: Toxicity Assessment Bot</a> |
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""", |
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unsafe_allow_html=True, |
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) |
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