Changed the size if statement

utils.py

@@ -112,7 +112,7 @@ def add_new_eval(
 
     upload_data = json.loads(input_file)
     print("upload_data:\n", upload_data)
-    data_row = [f'{upload_data["Model"]}', upload_data['Overall']]
+    data_row = [f'{upload_data["Model"]}', upload_data['DP Acc']]
     print("data_row:\n", data_row)
     submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL,
                                  use_auth_token=HF_TOKEN, repo_type="dataset")
@@ -146,7 +146,7 @@ def search_and_filter_models(df, query, min_size, max_size):
         filtered_df = filtered_df[filtered_df['Models'].str.contains(query, case=False, na=False)]
 
     size_mask = filtered_df['Model Size(B)'].apply(lambda x: 
-        (min_size <= 1000.0 <= max_size) if x == 'unknown' 
+        (min_size <= 1000.0 <= max_size) if x == 'unknown' or x == '-' or x == 'unk' 
         else (min_size <= x <= max_size))
     
     filtered_df = filtered_df[size_mask]
@@ -184,7 +184,7 @@ def search_models(df, query):
 
 
 def get_size_range(df):
-    sizes = df['Model Size(B)'].apply(lambda x: 1000.0 if x == 'unknown' else x)
+    sizes = df['Model Size(B)'].apply(lambda x: 1000.0 if x == 'unknown'  or x == '-' or x == 'unk' else x)
     return float(sizes.min()), float(sizes.max())
 
 
@@ -196,16 +196,3 @@ def process_model_size(size):
         return val
     except (ValueError, TypeError):
         return 'unknown'
-
-
-def filter_columns_by_subjects(df, selected_subjects=None):
-    if selected_subjects is None or len(selected_subjects) == 0:
-        return df[COLUMN_NAMES]
-    
-    base_columns = ['Models', 'Model Size(B)', 'Data Source', 'DP Acc']
-    selected_columns = base_columns + selected_subjects
-    
-    available_columns = [col for col in selected_columns if col in df.columns]
-    return df[available_columns]
-
-