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Commit
511bdd4
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Add basic app based on ECCV

Browse files
__pycache__/model_list.cpython-311.pyc ADDED
Binary file (5.55 kB). View file
 
app.py ADDED
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+ #!/usr/bin/env python
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+
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+ from __future__ import annotations
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+
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+ import gradio as gr
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+
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+ from model_list import ModelList
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+
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+ DESCRIPTION = '# Clinical & Biomedical Language Models'
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+ NOTES = '''
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+ - Stanford HAI Article, ["The Shaky Foundations of Foundation Models in Healthcare"](https://hai.stanford.edu/news/shaky-foundations-foundation-models-healthcare)
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+ '''
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+ FOOTER = ''''''
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+
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+ def main():
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+ model_list = ModelList()
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+
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+ with gr.Blocks(css='style.css') as demo:
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+ gr.Markdown(DESCRIPTION)
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+
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+ search_box = gr.Textbox(
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+ label='Search Model Name',
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+ placeholder=
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+ 'You can search for titles with regular expressions. e.g. (?<!sur)face',
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+ max_lines=1)
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+ case_sensitive = gr.Checkbox(label='Case Sensitive')
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+ filter_names = gr.CheckboxGroup(choices=[
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+ 'Paper',
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+ 'Code',
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+ 'Model Weights',
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+ ], label='Filter')
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+
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+ data_type_names = [
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+ 'Biomedical',
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+ 'Clinical',
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+ 'Scientific',
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+ ]
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+
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+ # prev: paper_sessions
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+ data_types = gr.CheckboxGroup(choices=data_type_names,
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+ value=data_type_names,
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+ label='Training Data Type(s)')
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+ search_button = gr.Button('Search')
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+
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+ number_of_models = gr.Textbox(label='Number of Models Found')
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+ table = gr.HTML(show_label=False)
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+
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+ gr.Markdown(NOTES)
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+ gr.Markdown(FOOTER)
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+
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+ demo.load(fn=model_list.render,
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+ inputs=[
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+ search_box,
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+ case_sensitive,
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+ filter_names,
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+ data_types,
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+ ],
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+ outputs=[
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+ number_of_models,
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+ table,
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+ ])
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+ search_box.submit(fn=model_list.render,
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+ inputs=[
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+ search_box,
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+ case_sensitive,
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+ filter_names,
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+ data_types,
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+ ],
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+ outputs=[
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+ number_of_models,
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+ table,
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+ ])
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+
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+ search_button.click(fn=model_list.render,
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+ inputs=[
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+ search_box,
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+ case_sensitive,
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+ filter_names,
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+ data_types,
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+ ],
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+ outputs=[
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+ number_of_models,
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+ table,
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+ ])
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+
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+ demo.launch(enable_queue=True, share=False)
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+
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+
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+ if __name__ == '__main__':
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+ main()
model_list.py ADDED
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+ from __future__ import annotations
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+
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+ import numpy as np
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+ import pandas as pd
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+ import requests
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+ from huggingface_hub.hf_api import SpaceInfo
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+
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+ url = 'https://docs.google.com/spreadsheets/d/1fANyV8spnEGUBMevjnb1FupkbESq9lTM2CGQt413sXQ/edit#gid=874079331'
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+ csv_url = url.replace('/edit#gid=', '/export?format=csv&gid=')
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+
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+ class ModelList:
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+ def __init__(self):
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+ self.table = pd.read_csv(csv_url)
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+ self._preprocess_table()
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+
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+ self.table_header = '''
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+ <tr>
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+ <td width="40%">Model Name</td>
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+ <td width="10%">Data Type(s)</td>
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+ <td width="10%">Year Published</td>
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+ <td width="10%">Paper</td>
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+ <td width="10%">Code on Github</td>
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+ <td width="10%">Weights on 🤗</td>
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+ <td width="10%">Other Weights</td>
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+ </tr>'''
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+
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+ def _preprocess_table(self) -> None:
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+ self.table['name_lowercase'] = self.table.name.str.lower()
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+
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+ rows = []
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+ for row in self.table.itertuples():
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+ paper = f'<a href="{row.paper}" target="_blank">Paper</a>' if isinstance(
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+ row.paper, str) else ''
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+ github = f'<a href="{row.github}" target="_blank">GitHub</a>' if isinstance(
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+ row.github, str) else ''
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+ hf_model = f'<a href="{row.hub}" target="_blank">Hub Model</a>' if isinstance(
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+ row.hub, str) else ''
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+ other_model = f'<a href="{row.other}" target="_blank">Other Weights</a>' if isinstance(
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+ row.other, str) else ''
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+ row = f'''
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+ <tr>
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+ <td>{row.name}</td>
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+ <td>{row.type}</td>
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+ <td>{row.year}</td>
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+ <td>{paper}</td>
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+ <td>{github}</td>
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+ <td>{hf_model}</td>
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+ <td>{other_model}</td>
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+ </tr>'''
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+ rows.append(row)
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+ self.table['html_table_content'] = rows
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+
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+ def render(self, search_query: str, case_sensitive: bool,
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+ filter_names: list[str],
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+ data_types: list[str]) -> tuple[int, str]:
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+ df = self.table
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+ if search_query:
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+ if case_sensitive:
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+ df = df[df.name.str.contains(search_query)]
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+ else:
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+ df = df[df.name_lowercase.str.contains(search_query.lower())]
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+ has_paper = 'Paper' in filter_names
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+ has_github = 'Github' in filter_names
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+ has_model = 'Hub Model' in filter_names or 'Other Weights' in filter_names
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+ df = self.filter_table(df, has_paper, has_github, has_model, data_types)
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+ return len(df), self.to_html(df, self.table_header)
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+
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+ @staticmethod
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+ def filter_table(df: pd.DataFrame, has_paper: bool, has_github: bool,
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+ has_model: bool,
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+ data_types: list[str]) -> pd.DataFrame:
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+ if has_paper:
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+ df = df[~df.paper.isna()]
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+ if has_github:
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+ df = df[~df.github.isna()]
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+ if has_model:
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+ df = df[~df.hub.isna() | ~df.other.isna()]
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+ df = df[df.type.isin(set(data_types))]
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+ return df
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+
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+ @staticmethod
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+ def to_html(df: pd.DataFrame, table_header: str) -> str:
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+ table_data = ''.join(df.html_table_content)
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+ html = f'''
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+ <table>
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+ {table_header}
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+ {table_data}
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+ </table>'''
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+ return html
requirements.txt ADDED
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+ gradio
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+ pandas
style.css ADDED
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+ h1 {
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+ text-align: center;
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+ }
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+ table a {
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+ background-color: transparent;
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+ color: #58a6ff;
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+ text-decoration: none;
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+ }
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+ a:active,
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+ a:hover {
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+ outline-width: 0;
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+ }
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+ a:hover {
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+ text-decoration: underline;
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+ }
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+ table, th, td {
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+ border: 1px solid;
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+ }
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+
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+