DontPlanToEnd
commited on
Commit
•
11f5f93
1
Parent(s):
915b360
Update app.py
Browse files
app.py
CHANGED
@@ -54,9 +54,9 @@ def update_table(df: pd.DataFrame, query: str, param_ranges: dict) -> pd.DataFra
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return filtered_df[UGI_COLS] # Return only the columns defined in UGI_COLS
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# Define the Gradio interface
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-
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with
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gr.HTML("""<h1 align="center">UGI Leaderboard</h1>""")
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gr.Markdown("""
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UGI: Uncensored General Intelligence. The average of 5 different subjects that LLMs are commonly steered away from. The leaderboard is made from roughly 60 questions overall, measuring both "willingness to answer" and "accuracy" in fact-based controversial questions.
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@@ -80,7 +80,7 @@ with demo:
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filter_columns_size = gr.CheckboxGroup(
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label="Model sizes (in billions of parameters)",
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choices=['~1.5', '~3', '~7', '~13', '~20', '~34', '~50', '~70+'],
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value=[
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interactive=True,
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elem_id="filter-columns-size",
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)
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@@ -120,4 +120,4 @@ with demo:
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)
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# Launch the Gradio app
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-
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return filtered_df[UGI_COLS] # Return only the columns defined in UGI_COLS
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# Define the Gradio interface
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GraInter = gr.Blocks()
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with GraInter:
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gr.HTML("""<h1 align="center">UGI Leaderboard</h1>""")
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gr.Markdown("""
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UGI: Uncensored General Intelligence. The average of 5 different subjects that LLMs are commonly steered away from. The leaderboard is made from roughly 60 questions overall, measuring both "willingness to answer" and "accuracy" in fact-based controversial questions.
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filter_columns_size = gr.CheckboxGroup(
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label="Model sizes (in billions of parameters)",
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choices=['~1.5', '~3', '~7', '~13', '~20', '~34', '~50', '~70+'],
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value=[], # Set the default value to an empty list
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interactive=True,
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elem_id="filter-columns-size",
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)
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)
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# Launch the Gradio app
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GraInter.launch()
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