Update stan_large.py

stan_large.py

@@ -37,9 +37,9 @@ which refers to the “Lionhead” video game company, was labeled as “lion he
 We therefore constructed the STAN large dataset of 12,594 hashtags with additional quality control for human annotations."
 """
 _URLS = {
-    "train": "https://github.com/prashantkodali/HashSet/raw/master/datasets/stan-large-maddela_et_al_train.pkl",
-    "dev": "https://github.com/prashantkodali/HashSet/raw/master/datasets/stan-large-maddela_et_al_dev.pkl",
-    "test": "https://github.com/prashantkodali/HashSet/raw/master/datasets/stan-large-maddela_et_al_test.pkl"
+    "train": "https://raw.githubusercontent.com/ruanchaves/hashformers/master/datasets/stan_large_train.csv",
+    "dev": "https://raw.githubusercontent.com/ruanchaves/hashformers/master/datasets/stan_large_dev.csv",
+    "test": "https://raw.githubusercontent.com/ruanchaves/hashformers/master/datasets/stan_large_test.csv"
 }
 
 class StanLarge(datasets.GeneratorBasedBuilder):
@@ -100,20 +100,7 @@ class StanLarge(datasets.GeneratorBasedBuilder):
             alts = [{"segmentation": x} for x in alts]
             return alts
 
-        with open(filepath, 'rb') as f:
-            try:
-                import pickle
-                records = pickle.load(f)
-            except ValueError:
-                try:
-                    import pickle5 as pickle
-                    records = pickle.load(f)
-                except ModuleNotFoundError:
-                    raise ImportError(
-                        """To be able to use stan_large, you need to install the following dependencies['pickle5'] 
-                        using 'pip install pickle5' for instance"""
-                    )
-        records = records.to_dict("records")
+        records = pd.read_csv(filepath).to_dict("records")
         for idx, row in enumerate(records):
             segmentation = get_segmentation(row)
             alternatives = get_alternatives(row, segmentation)