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CPU Upgrade
Running
on
CPU Upgrade
removed filters and columns we dont need
Browse files- app.py +25 -25
- src/display/utils.py +7 -7
- src/leaderboard/read_evals.py +7 -7
app.py
CHANGED
@@ -144,10 +144,10 @@ with demo:
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elem_id="column-select",
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interactive=True,
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)
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with gr.Row():
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deleted_models_visibility = gr.Checkbox(
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value=False, label="Show gated/private/deleted models", interactive=True
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)
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with gr.Column(min_width=320):
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#with gr.Box(elem_id="box-filter"):
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filter_columns_type = gr.CheckboxGroup(
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@@ -157,20 +157,20 @@ with demo:
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interactive=True,
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elem_id="filter-columns-type",
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)
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filter_columns_precision = gr.CheckboxGroup(
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)
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filter_columns_size = gr.CheckboxGroup(
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)
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leaderboard_table = gr.components.Dataframe(
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value=leaderboard_df[
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@@ -199,23 +199,23 @@ with demo:
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hidden_leaderboard_table_for_search,
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shown_columns,
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filter_columns_type,
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filter_columns_precision,
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filter_columns_size,
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deleted_models_visibility,
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search_bar,
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],
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leaderboard_table,
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)
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for selector in [shown_columns, filter_columns_type
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selector.change(
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update_table,
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[
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hidden_leaderboard_table_for_search,
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shown_columns,
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filter_columns_type,
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filter_columns_precision,
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filter_columns_size,
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deleted_models_visibility,
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search_bar,
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],
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leaderboard_table,
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elem_id="column-select",
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interactive=True,
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)
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+
# with gr.Row():
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# deleted_models_visibility = gr.Checkbox(
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# value=False, label="Show gated/private/deleted models", interactive=True
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# )
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with gr.Column(min_width=320):
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#with gr.Box(elem_id="box-filter"):
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filter_columns_type = gr.CheckboxGroup(
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interactive=True,
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elem_id="filter-columns-type",
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)
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# filter_columns_precision = gr.CheckboxGroup(
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# label="Precision",
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# choices=[i.value.name for i in utils.Precision],
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# value=[i.value.name for i in utils.Precision],
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# interactive=True,
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# elem_id="filter-columns-precision",
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# )
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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=list(utils.NUMERIC_INTERVALS.keys()),
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# value=list(utils.NUMERIC_INTERVALS.keys()),
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# interactive=True,
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# elem_id="filter-columns-size",
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# )
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leaderboard_table = gr.components.Dataframe(
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value=leaderboard_df[
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hidden_leaderboard_table_for_search,
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shown_columns,
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filter_columns_type,
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# filter_columns_precision,
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# filter_columns_size,
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# deleted_models_visibility,
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search_bar,
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],
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leaderboard_table,
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)
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for selector in [shown_columns, filter_columns_type]: #, filter_columns_precision, filter_columns_size, deleted_models_visibility]:
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selector.change(
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update_table,
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[
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hidden_leaderboard_table_for_search,
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shown_columns,
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filter_columns_type,
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# filter_columns_precision,
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# filter_columns_size,
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# deleted_models_visibility,
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search_bar,
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],
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leaderboard_table,
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src/display/utils.py
CHANGED
@@ -33,14 +33,14 @@ for task in Tasks:
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# Model information
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auto_eval_column_dict.append(["model_type", ColumnContent, ColumnContent("Type", "str", False)])
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auto_eval_column_dict.append(["architecture", ColumnContent, ColumnContent("Architecture", "str", False)])
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auto_eval_column_dict.append(["weight_type", ColumnContent, ColumnContent("Weight type", "str", False, True)])
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auto_eval_column_dict.append(["precision", ColumnContent, ColumnContent("Precision", "str", False)])
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auto_eval_column_dict.append(["license", ColumnContent, ColumnContent("Hub License", "str", False)])
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auto_eval_column_dict.append(["params", ColumnContent, ColumnContent("#Params (B)", "number", False)])
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auto_eval_column_dict.append(["likes", ColumnContent, ColumnContent("Hub ❤️", "number", False)])
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auto_eval_column_dict.append(["still_on_hub", ColumnContent, ColumnContent("Available on the hub", "bool", False)])
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auto_eval_column_dict.append(["revision", ColumnContent, ColumnContent("Model sha", "str", False, False)])
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# Dummy column for the search bar (hidden by the custom CSS)
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auto_eval_column_dict.append(["dummy", ColumnContent, ColumnContent("model_name_for_query", "str", False, dummy=True)])
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# Model information
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auto_eval_column_dict.append(["model_type", ColumnContent, ColumnContent("Type", "str", False)])
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#auto_eval_column_dict.append(["architecture", ColumnContent, ColumnContent("Architecture", "str", False)])
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auto_eval_column_dict.append(["weight_type", ColumnContent, ColumnContent("Weight type", "str", False, True)])
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#auto_eval_column_dict.append(["precision", ColumnContent, ColumnContent("Precision", "str", False)])
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#auto_eval_column_dict.append(["license", ColumnContent, ColumnContent("Hub License", "str", False)])
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#auto_eval_column_dict.append(["params", ColumnContent, ColumnContent("#Params (B)", "number", False)])
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#auto_eval_column_dict.append(["likes", ColumnContent, ColumnContent("Hub ❤️", "number", False)])
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#auto_eval_column_dict.append(["still_on_hub", ColumnContent, ColumnContent("Available on the hub", "bool", False)])
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#auto_eval_column_dict.append(["revision", ColumnContent, ColumnContent("Model sha", "str", False, False)])
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# Dummy column for the search bar (hidden by the custom CSS)
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auto_eval_column_dict.append(["dummy", ColumnContent, ColumnContent("model_name_for_query", "str", False, dummy=True)])
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src/leaderboard/read_evals.py
CHANGED
@@ -104,18 +104,18 @@ class EvalResult:
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data_dict = {
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"eval_name": self.eval_name, # not a column, just a save name,
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utils.AutoEvalColumn.precision.name: self.precision.value.name,
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utils.AutoEvalColumn.model_type.name: self.model_type.value.name,
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utils.AutoEvalColumn.model_type_symbol.name: self.model_type.value.symbol,
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utils.AutoEvalColumn.weight_type.name: self.weight_type.value.name,
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utils.AutoEvalColumn.architecture.name: self.architecture,
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utils.AutoEvalColumn.model.name: formatting.make_clickable_model(self.full_model),
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utils.AutoEvalColumn.dummy.name: self.full_model,
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utils.AutoEvalColumn.revision.name: self.revision,
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utils.AutoEvalColumn.license.name: self.license,
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utils.AutoEvalColumn.likes.name: self.likes,
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utils.AutoEvalColumn.params.name: self.num_params,
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utils.AutoEvalColumn.still_on_hub.name: self.still_on_hub,
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}
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for task in utils.Tasks:
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data_dict = {
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"eval_name": self.eval_name, # not a column, just a save name,
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# utils.AutoEvalColumn.precision.name: self.precision.value.name,
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utils.AutoEvalColumn.model_type.name: self.model_type.value.name,
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utils.AutoEvalColumn.model_type_symbol.name: self.model_type.value.symbol,
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utils.AutoEvalColumn.weight_type.name: self.weight_type.value.name,
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# utils.AutoEvalColumn.architecture.name: self.architecture,
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utils.AutoEvalColumn.model.name: formatting.make_clickable_model(self.full_model),
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utils.AutoEvalColumn.dummy.name: self.full_model,
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# utils.AutoEvalColumn.revision.name: self.revision,
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# utils.AutoEvalColumn.license.name: self.license,
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# utils.AutoEvalColumn.likes.name: self.likes,
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# utils.AutoEvalColumn.params.name: self.num_params,
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# utils.AutoEvalColumn.still_on_hub.name: self.still_on_hub,
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}
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for task in utils.Tasks:
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