Update data path, holds updated data.

dataset_infos.json

@@ -1 +0,0 @@
-{"default": {"description": "OneStopQA is a multiple choice reading comprehension dataset annotated according to the STARC (Structured Annotations for Reading Comprehension) scheme. The reading materials are Guardian articles taken from the [OneStopEnglish corpus](https://github.com/nishkalavallabhi/OneStopEnglishCorpus). Each article comes in three difficulty levels, Elementary, Intermediate and Advanced. Each paragraph is annotated with three multiple choice reading comprehension questions. The reading comprehension questions can be answered based on any of the three paragraph levels.\n", "citation": "@inproceedings{starc2020,\n      author    = {Berzak, Yevgeni and Malmaud, Jonathan and Levy, Roger},\n      title     = {STARC: Structured Annotations for Reading Comprehension},\n      booktitle = {ACL},\n      year      = {2020},\n      publisher = {Association for Computational Linguistics}\n      }\n", "homepage": "https://github.com/berzak/onestop-qa", "license": "Creative Commons Attribution-ShareAlike 4.0 International License", "features": {"title": {"dtype": "string", "id": null, "_type": "Value"}, "paragraph": {"dtype": "string", "id": null, "_type": "Value"}, "level": {"num_classes": 3, "names": ["Adv", "Int", "Ele"], "names_file": null, "id": null, "_type": "ClassLabel"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "paragraph_index": {"dtype": "int32", "id": null, "_type": "Value"}, "answers": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": 4, "id": null, "_type": "Sequence"}, "a_span": {"feature": {"dtype": "int32", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "d_span": {"feature": {"dtype": "int32", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": [], "builder_name": "one_stop_qa", "config_name": "default", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1423090, "num_examples": 1458, "dataset_name": "one_stop_qa"}}, "download_checksums": {"https://github.com/berzak/onestop-qa/raw/master/annotations/onestop_qa.zip": {"num_bytes": 118173, "checksum": "4e9baf4c09797505f7841466d06f521c3d675f7855a987b96c1b3d1fe9ada1ff"}}, "download_size": 118173, "post_processing_size": null, "dataset_size": 1423090, "size_in_bytes": 1541263}}

onestop_qa.py

@@ -55,14 +55,14 @@ _LICENSE = "Creative Commons Attribution-ShareAlike 4.0 International License"
 
 # The HuggingFace dataset library don't host the datasets but only point to the original files
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
-_URL = "https://github.com/berzak/onestop-qa/raw/master/annotations/onestop_qa.zip"
+_URL = "https://github.com/berzak/onestop-qa/raw/zip_for_hf/annotations/onestop_qa.zip"
 
 
 class OneStopQA(datasets.GeneratorBasedBuilder):
     """OneStopQA - a multiple choice reading comprehension dataset annotated
     according to the STARC (Structured Annotations for Reading Comprehension) scheme"""
 
-    VERSION = datasets.Version("1.1.0")
+    VERSION = datasets.Version("1.1.1")
 
     # This is an example of a dataset with multiple configurations.
     # If you don't want/need to define several sub-sets in your dataset,