Update Test.py

Test.py

@@ -7,23 +7,8 @@ logger = datasets.logging.get_logger(__name__)
 _VERSION = "1.0.0"
 _NAME = "qa_harvesting_from_wikipedia"
 _DESCRIPTION = """QA pairs generated in https://aclanthology.org/P18-1177/"""
-_CITATION = """
-@inproceedings{du-cardie-2018-harvesting,
-    title = "Harvesting Paragraph-level Question-Answer Pairs from {W}ikipedia",
-    author = "Du, Xinya  and
-      Cardie, Claire",
-    booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
-    month = jul,
-    year = "2018",
-    address = "Melbourne, Australia",
-    publisher = "Association for Computational Linguistics",
-    url = "https://aclanthology.org/P18-1177",
-    doi = "10.18653/v1/P18-1177",
-    pages = "1907--1917",
-    abstract = "We study the task of generating from Wikipedia articles question-answer pairs that cover content beyond a single sentence. We propose a neural network approach that incorporates coreference knowledge via a novel gating mechanism. As compared to models that only take into account sentence-level information (Heilman and Smith, 2010; Du et al., 2017; Zhou et al., 2017), we find that the linguistic knowledge introduced by the coreference representation aids question generation significantly, producing models that outperform the current state-of-the-art. We apply our system (composed of an answer span extraction system and the passage-level QG system) to the 10,000 top ranking Wikipedia articles and create a corpus of over one million question-answer pairs. We provide qualitative analysis for the this large-scale generated corpus from Wikipedia.",
-}
-"""
-_BASE_URL = "https://huggingface.co/datasets/lmqg/qa_harvesting_from_wikipedia/resolve/main/dataset"
+_CITATION = ""
+_BASE_URL = "https://huggingface.co/datasets/DrakuTheDragon/Test/tree/main"
 _URLS = {
     str(datasets.Split.TEST): f'{_BASE_URL}/test.json'
 }