Upload id_short_answer_grading.py with huggingface_hub

id_short_answer_grading.py

@@ -4,11 +4,11 @@ from typing import Dict, List, Tuple
 
 import datasets
 
-from nusacrowd.nusa_datasets.id_short_answer_grading.utils.id_short_answer_grading_utils import \
+from seacrowd.sea_datasets.id_short_answer_grading.utils.id_short_answer_grading_utils import \
     create_saintek_and_soshum_dataset
-from nusacrowd.utils import schemas
-from nusacrowd.utils.configs import NusantaraConfig
-from nusacrowd.utils.constants import Tasks
+from seacrowd.utils import schemas
+from seacrowd.utils.configs import SEACrowdConfig
+from seacrowd.utils.constants import Tasks
 
 _CITATION = """\
 @article{
@@ -72,28 +72,28 @@ _SUPPORTED_TASKS = [Tasks.SHORT_ANSWER_GRADING]
 
 _SOURCE_VERSION = "1.0.0"
 
-_NUSANTARA_VERSION = "1.0.0"
+_SEACROWD_VERSION = "2024.06.20"
 
 
 class IdShortAnswerGrading(datasets.GeneratorBasedBuilder):
     """Indonesian short answers for Biology and Geography subjects from 534 respondents where the answer grading was done by 7 experts."""
 
     SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
-    NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION)
+    SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION)
 
     BUILDER_CONFIGS = [
-        NusantaraConfig(
+        SEACrowdConfig(
             name="id_short_answer_grading_source",
             version=SOURCE_VERSION,
             description="id_short_answer_grading source schema",
             schema="source",
             subset_id="id_short_answer_grading",
         ),
-        NusantaraConfig(
-            name="id_short_answer_grading_nusantara_pairs_score",
-            version=NUSANTARA_VERSION,
+        SEACrowdConfig(
+            name="id_short_answer_grading_seacrowd_pairs_score",
+            version=SEACROWD_VERSION,
             description="id_short_answer_grading Nusantara schema",
-            schema="nusantara_pairs_score",
+            schema="seacrowd_pairs_score",
             subset_id="id_short_answer_grading",
         ),
     ]
@@ -112,7 +112,7 @@ class IdShortAnswerGrading(datasets.GeneratorBasedBuilder):
                     "score": datasets.Value("int64"),
                 }
             )
-        elif self.config.schema == "nusantara_pairs_score":
+        elif self.config.schema == "seacrowd_pairs_score":
             features = schemas.pairs_features([0, 1, 2, 3, 4, 5])
 
         return datasets.DatasetInfo(
@@ -184,7 +184,7 @@ class IdShortAnswerGrading(datasets.GeneratorBasedBuilder):
                 }
                 yield row.index, entry
 
-        elif self.config.schema == "nusantara_pairs_score":
+        elif self.config.schema == "seacrowd_pairs_score":
             for row in df.itertuples():
                 entry = {
                     "id": str(row.index),