fix ModelType is not defined

src/display/utils.py

@@ -166,31 +166,6 @@ human_baseline_row[AutoEvalColumn.npm.name] = round(sum(npm) / len(npm), 2)
 if GET_ORIGINAL_HF_LEADERBOARD_EVAL_RESULTS:
     human_baseline_row["🤗 Leaderboard Average"] = None
 
-#External models
-external_rows = []
-if os.path.exists('external_models_results.json'):
-    with open('external_models_results.json', 'r', encoding='utf8') as f:
-        all_models = json.load(f)
-    for model_data in all_models:
-        model_row = deepcopy(baseline_row)
-        model_row[AutoEvalColumn.model.name] = f'<a target="_blank" href="{model_data["link"]}" style="color: var(--text-color); text-decoration: underline;text-decoration-style: dotted;">{model_data["name"]} [{model_data["date"]}]</a>'
-        model_row[AutoEvalColumn.dummy.name] = model_data['model']
-        for task in Tasks:
-            model_row[task.value.col_name] = round(model_data['result_metrics'][task.value.benchmark]*100, 2)
-        model_row[AutoEvalColumn.average.name] = round(model_data['result_metrics_average']*100, 2)
-        model_row[AutoEvalColumn.npm.name] = round(model_data['result_metrics_npm']*100, 2)
-        
-        model_type = ModelType.from_str(model_data['model_type'])
-        model_row[AutoEvalColumn.model_type.name] = model_type.name
-        model_row[AutoEvalColumn.model_type_symbol.name] = model_type.symbol
-        if model_type == ModelType.proprietary:
-            model_row[AutoEvalColumn.license.name] = "Proprietary"
-        if 'params' in model_data:
-            model_row[AutoEvalColumn.params.name] = model_data['params']
-
-        model_row[AutoEvalColumn.main_language.name] = model_data['main_language']
-        external_rows.append(model_row)
-
 @dataclass
 class ModelDetails:
     name: str
@@ -273,6 +248,31 @@ class Language(Enum):
             return Language.Other
         return Language.Unknown
 
+#External models
+external_rows = []
+if os.path.exists('external_models_results.json'):
+    with open('external_models_results.json', 'r', encoding='utf8') as f:
+        all_models = json.load(f)
+    for model_data in all_models:
+        model_row = deepcopy(baseline_row)
+        model_row[AutoEvalColumn.model.name] = f'<a target="_blank" href="{model_data["link"]}" style="color: var(--text-color); text-decoration: underline;text-decoration-style: dotted;">{model_data["name"]} [{model_data["date"]}]</a>'
+        model_row[AutoEvalColumn.dummy.name] = model_data['model']
+        for task in Tasks:
+            model_row[task.value.col_name] = round(model_data['result_metrics'][task.value.benchmark]*100, 2)
+        model_row[AutoEvalColumn.average.name] = round(model_data['result_metrics_average']*100, 2)
+        model_row[AutoEvalColumn.npm.name] = round(model_data['result_metrics_npm']*100, 2)
+        
+        model_type = ModelType.from_str(model_data['model_type'])
+        model_row[AutoEvalColumn.model_type.name] = model_type.name
+        model_row[AutoEvalColumn.model_type_symbol.name] = model_type.symbol
+        if model_type == ModelType.proprietary:
+            model_row[AutoEvalColumn.license.name] = "Proprietary"
+        if 'params' in model_data:
+            model_row[AutoEvalColumn.params.name] = model_data['params']
+
+        model_row[AutoEvalColumn.main_language.name] = model_data['main_language']
+        external_rows.append(model_row)
+
 
 # Column selection
 COLS = [c.name for c in fields(AutoEvalColumn)]