Test

src/leaderboard/read_evals.py

@@ -21,7 +21,7 @@ class EvalResult:
     model: str
     revision: str  # commit hash, "" if main
     results: dict
-    precision: Precision = Precision.Unknown
+    precision: str = "float16"
     model_type: ModelType = ModelType.Unknown  # Pretrained, fine tuned, ...
     weight_type: WeightType = WeightType.Original  # Original or Adapter
     architecture: str = "Unknown"
@@ -51,11 +51,11 @@ class EvalResult:
         if len(org_and_model) == 1:
             org = None
             model = org_and_model[0]
-            result_key = f"{model}_{precision.value.name}"
+            result_key = f"{model}_{precision}"
         else:
             org = org_and_model[0]
             model = org_and_model[1]
-            result_key = f"{org}_{model}_{precision.value.name}"
+            result_key = f"{org}_{model}_{precision}"
         full_model = "/".join(org_and_model)
 
         still_on_hub, _, model_config = is_model_on_hub(
@@ -107,7 +107,7 @@ class EvalResult:
             self.date = request.get("submitted_time", "")
         except Exception:
             print(
-                f"Could not find request file for {self.org}/{self.model} with precision {self.precision.value.name}"
+                f"Could not find request file for {self.org}/{self.model} with precision {self.precision}"
             )
 
     def to_dict(self):
@@ -115,7 +115,7 @@ class EvalResult:
         average = sum([v for v in self.results.values() if v is not None]) / len(Tasks)
         data_dict = {
             "eval_name": self.eval_name,  # not a column, just a save name,
-            AutoEvalColumn.precision.name: self.precision.value.name,
+            AutoEvalColumn.precision.name: self.precision,
             AutoEvalColumn.model_type.name: self.model_type.value.name,
             AutoEvalColumn.model_type_symbol.name: self.model_type.value.symbol,
             AutoEvalColumn.weight_type.name: self.weight_type.value.name,