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CPU Upgrade
Clémentine
commited on
Commit
•
ecef2dc
1
Parent(s):
613696b
updated design to select columns to display
Browse files- app.py +28 -38
- src/utils_display.py +1 -1
app.py
CHANGED
@@ -259,16 +259,22 @@ def refresh():
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def search_table(df, query):
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if AutoEvalColumn.model_type.name in
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filtered_df = df[
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(df[AutoEvalColumn.dummy.name].str.contains(query, case=False))
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| (df[AutoEvalColumn.model_type.name].str.contains(query, case=False))
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]
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else:
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filtered_df = df[(df[AutoEvalColumn.dummy.name].str.contains(query, case=False))]
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return filtered_df
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def change_tab(query_param):
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query_param = query_param.replace("'", '"')
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@@ -288,44 +294,30 @@ demo = gr.Blocks(css=custom_css)
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with demo:
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gr.HTML(TITLE)
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gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
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with gr.Row():
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with gr.Box(elem_id="search-bar-table-box"):
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search_bar = gr.Textbox(
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placeholder="🔍 Search your model and press ENTER...",
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show_label=False,
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elem_id="search-bar",
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)
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with gr.Tabs(elem_classes="tab-buttons") as tabs:
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with gr.TabItem("🏅 LLM Benchmark", elem_id="llm-benchmark-tab-table", id=0):
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visible=False,
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)
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search_bar.submit(
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search_table,
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[hidden_leaderboard_table_for_search_lite, search_bar],
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leaderboard_table_lite,
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)
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with gr.TabItem("🔍 Extended model view", elem_id="llm-benchmark-tab-table", id=1):
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leaderboard_table = gr.components.Dataframe(
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value=leaderboard_df,
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headers=
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datatype=TYPES,
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max_rows=None,
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elem_id="leaderboard-table",
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)
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# Dummy leaderboard for handling the case when the user uses backspace key
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@@ -338,9 +330,10 @@ with demo:
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)
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search_bar.submit(
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search_table,
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[hidden_leaderboard_table_for_search, search_bar],
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leaderboard_table,
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)
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with gr.TabItem("📝 About", elem_id="llm-benchmark-tab-table", id=2):
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gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="markdown-text")
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@@ -392,7 +385,6 @@ with demo:
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label="Model type",
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multiselect=False,
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value="pretrained",
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max_choices=1,
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interactive=True,
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)
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@@ -402,7 +394,6 @@ with demo:
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label="Precision",
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multiselect=False,
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value="float16",
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max_choices=1,
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interactive=True,
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)
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weight_type = gr.Dropdown(
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@@ -410,7 +401,6 @@ with demo:
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label="Weights type",
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multiselect=False,
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value="Original",
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max_choices=1,
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interactive=True,
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)
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base_model_name_textbox = gr.Textbox(
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)
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def search_table(df, leaderboard_table, query):
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if AutoEvalColumn.model_type.name in leaderboard_table.columns:
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filtered_df = df[
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(df[AutoEvalColumn.dummy.name].str.contains(query, case=False))
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| (df[AutoEvalColumn.model_type.name].str.contains(query, case=False))
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]
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else:
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filtered_df = df[(df[AutoEvalColumn.dummy.name].str.contains(query, case=False))]
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return filtered_df[leaderboard_table.columns]
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def select_columns(df, columns):
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always_here_cols = [AutoEvalColumn.model_type_symbol.name, AutoEvalColumn.model.name]
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# We use COLS to maintain sorting
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filtered_df = df[always_here_cols + [c for c in COLS if c in df.columns and c in columns] + [AutoEvalColumn.dummy.name]]
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return filtered_df
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def change_tab(query_param):
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query_param = query_param.replace("'", '"')
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with demo:
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gr.HTML(TITLE)
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gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
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with gr.Tabs(elem_classes="tab-buttons") as tabs:
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with gr.TabItem("🏅 LLM Benchmark", elem_id="llm-benchmark-tab-table", id=0):
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with gr.Row():
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shown_columns = gr.CheckboxGroup(
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choices = [c for c in COLS if c not in [AutoEvalColumn.dummy.name, AutoEvalColumn.model.name, AutoEvalColumn.model_type_symbol.name]],
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value = [c for c in COLS_LITE if c not in [AutoEvalColumn.dummy.name, AutoEvalColumn.model.name, AutoEvalColumn.model_type_symbol.name]],
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label="Select columns to show",
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elem_id="column-select",
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interactive=True,
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)
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search_bar = gr.Textbox(
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placeholder="🔍 Search for your model and press ENTER...",
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show_label=False,
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elem_id="search-bar",
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)
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leaderboard_table = gr.components.Dataframe(
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value=leaderboard_df[[AutoEvalColumn.model_type_symbol.name, AutoEvalColumn.model.name] + shown_columns.value+ [AutoEvalColumn.dummy.name]],
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headers=[AutoEvalColumn.model_type_symbol.name, AutoEvalColumn.model.name] + shown_columns.value + [AutoEvalColumn.dummy.name],
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datatype=TYPES,
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max_rows=None,
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elem_id="leaderboard-table",
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interactive=False,
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visible=True,
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)
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# Dummy leaderboard for handling the case when the user uses backspace key
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)
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search_bar.submit(
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search_table,
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[hidden_leaderboard_table_for_search, leaderboard_table, search_bar],
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leaderboard_table,
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)
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shown_columns.change(select_columns, [hidden_leaderboard_table_for_search, shown_columns], leaderboard_table)
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with gr.TabItem("📝 About", elem_id="llm-benchmark-tab-table", id=2):
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gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="markdown-text")
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label="Model type",
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multiselect=False,
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value="pretrained",
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interactive=True,
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)
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label="Precision",
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multiselect=False,
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value="float16",
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interactive=True,
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)
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weight_type = gr.Dropdown(
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label="Weights type",
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multiselect=False,
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value="Original",
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interactive=True,
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)
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base_model_name_textbox = gr.Textbox(
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src/utils_display.py
CHANGED
@@ -20,7 +20,7 @@ class AutoEvalColumn: # Auto evals column
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arc = ColumnContent("ARC", "number", True)
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hellaswag = ColumnContent("HellaSwag", "number", True)
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mmlu = ColumnContent("MMLU", "number", True)
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truthfulqa = ColumnContent("TruthfulQA
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model_type = ColumnContent("Type", "str", False)
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precision = ColumnContent("Precision", "str", False, True)
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license = ColumnContent("Hub License", "str", False)
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arc = ColumnContent("ARC", "number", True)
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hellaswag = ColumnContent("HellaSwag", "number", True)
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mmlu = ColumnContent("MMLU", "number", True)
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truthfulqa = ColumnContent("TruthfulQA", "number", True)
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model_type = ColumnContent("Type", "str", False)
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precision = ColumnContent("Precision", "str", False, True)
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license = ColumnContent("Hub License", "str", False)
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