updata load script

the-vault-function.py

@@ -4,8 +4,29 @@ import pyarrow as pa
 import pyarrow.parquet as pq
 import datasets
 
+
+# Meta infomation
 _REPO_NAME = 'Fsoft-AIC/the-vault-function'
 
+_DESCRIPTION = """The Vault is a multilingual code-text dataset with over 40 million pairs covering 10 popular programming languages. 
+It is the largest corpus containing parallel code-text data. By building upon The Stack, a massive raw code sample collection, 
+the Vault offers a comprehensive and clean resource for advancing research in code understanding and generation. It provides a 
+high-quality dataset that includes code-text pairs at multiple levels, such as class and inline-level, in addition to the function level. 
+The Vault can serve many purposes at multiple levels."""
+
+_HOMEPAGE = "https://huggingface.co/Fsoft-AIC"
+_LICENSE = "MIT License"
+_CITATION = """
+@article{manh2023vault,
+  title={The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation},
+  author={Manh, Dung Nguyen and Hai, Nam Le and Dau, Anh TV and Nguyen, Anh Minh and Nghiem, Khanh and Guo, Jin and Bui, Nghi DQ},
+  journal={arXiv preprint arXiv:2305.06156},
+  year={2023}
+}
+"""
+###
+
+
 _LANG_TO_TEXT = {
     "python": "python",
     "c": "c",
@@ -17,26 +38,13 @@ _LANG_TO_TEXT = {
     "php": "php",
     "ruby": "ruby",
     "rust": "rust",
-}
-
-
-_DESCRIPTION = """The Vault is a multilingual code-text dataset with over 40 million pairs covering 10 popular programming languages. 
-It is the largest corpus containing parallel code-text data. By building upon The Stack, a massive raw code sample collection, 
-the Vault offers a comprehensive and clean resource for advancing research in code understanding and generation. It provides a 
-high-quality dataset that includes code-text pairs at multiple levels, such as class and inline-level, in addition to the function level. 
-The Vault can serve many purposes at multiple levels."""
-
-_HOMEPAGE = "https://huggingface.co/Fsoft-AIC"
-
+}       
+_LANG_CONFIGS = ["all"] + list(_LANG_TO_TEXT.keys())
 
 _TEXT_TO_LANG = {}
 for lang in _LANG_TO_TEXT:
     _TEXT_TO_LANG[_LANG_TO_TEXT[lang]] = lang
 
-
-        
-_LANG_CONFIGS = ["all"] + list(_LANG_TO_TEXT.keys())
-
 num_shard_split = {
     "train/small/ruby": 1,
     "train/small/c": 1,
@@ -218,6 +226,8 @@ class TheVaultFunction(datasets.GeneratorBasedBuilder):
                                         }),
             supervised_keys=None,
             homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
             
         )