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Browse files- src/display/utils.py +1 -1
- src/leaderboard/read_evals.py +3 -1
src/display/utils.py
CHANGED
@@ -52,7 +52,7 @@ auto_eval_column_dict.append(["still_on_hub", ColumnContent, ColumnContent("Avai
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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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-
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# We use make dataclass to dynamically fill the scores from Tasks
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AutoEvalColumn = make_dataclass("AutoEvalColumn", auto_eval_column_dict, frozen=True)
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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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+
auto_eval_column_dict.append(["rank", ColumnContent, ColumnContent("rank", "number", True, never_hidden=True)])
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# We use make dataclass to dynamically fill the scores from Tasks
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AutoEvalColumn = make_dataclass("AutoEvalColumn", auto_eval_column_dict, frozen=True)
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src/leaderboard/read_evals.py
CHANGED
@@ -266,7 +266,7 @@ class EvalResult:
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try:
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data_dict[AutoEvalColumn.model.name] = make_clickable_model(
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self.full_model, self.model) if self.still_on_hub else self.full_model
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except KeyError:
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print(f"Could not find model")
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@@ -354,6 +354,8 @@ class EvalResult:
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print(f"Could not find {task.value.col_name}")
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data_dict[task.value.col_name] = None
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return data_dict
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try:
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data_dict[AutoEvalColumn.model.name] = make_clickable_model(
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self.full_model, self.model) if self.still_on_hub else self.model #TODO or full_model
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except KeyError:
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print(f"Could not find model")
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print(f"Could not find {task.value.col_name}")
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data_dict[task.value.col_name] = None
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data_dict[AutoEvalColumn.rank.name] = 0
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return data_dict
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