add dataset_infos

dataset_infos.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:80797ddbd140d2dd54cee3675e901664c1e8dce4ffb80149d3ee9fa5c6513650
+size 1628

feedbackQA.py

@@ -35,12 +35,13 @@ It has two parts: the first part contains a conventional RQA dataset, \
 whilst this repo contains the second part, which contains feedback(ratings and natural language explanations) for QA pairs.
 """
 
-_URL = "https://drive.google.com/drive/folders/1mIcxZZ643k6SVJnZw1FmEOhndaFx4_PG?usp=sharing"
 #_URLS = {
-#    "train": _URL + "train-v1.1.json",
-#    "dev": _URL + "dev-v1.1.json",
+#    "train": "https://cdn-lfs.huggingface.co/datasets/McGill-NLP/FeedbackQA/46bd763229fc603d73f634a312367acb83c3b713a5dfd9fcf8a9b3e310c39a67",
+#    "dev": "https://cdn-lfs.huggingface.co/datasets/McGill-NLP/FeedbackQA/40a93282e5fdee4706c20e32ddd4734151139d67f6844dbcffb9e7be22ae6b8f",
+#    "test": "https://cdn-lfs.huggingface.co/datasets/McGill-NLP/FeedbackQA/50c4a21dc778cf064f731161e2213f21d2951cabd9331a1c524f791055040d02"
 #}
 
+_URL = 'https://drive.google.com/uc?export=download&id=14KV6yKgdjzb6fbFzshGuNvEp9zGv_gol'
 
 class FeedbackConfig(datasets.BuilderConfig):
     """BuilderConfig for FeedbackQA."""
@@ -92,12 +93,12 @@ class FeedbackQA(datasets.GeneratorBasedBuilder):
     def _split_generators(self, dl_manager):
         downloaded_files_path = dl_manager.download_and_extract(_URL)
         train_file = os.path.join(downloaded_files_path, 'feedback_train.json')
-        valid_file = os.path.join(downloaded_files_path, 'feedback_valid.json')
+        val_file = os.path.join(downloaded_files_path, 'feedback_valid.json')
         test_file = os.path.join(downloaded_files_path, 'feedback_test.json')
-
+        print(test_file)
         return [
             datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_file}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": valid_file}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": val_file}),
             datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_file}),
         ]