Delete loading script

medical_questions_pairs.py

@@ -1,83 +0,0 @@
-# coding=utf-8
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-"""Medical Question Pairs (MQP) Dataset"""
-
-
-import csv
-
-import datasets
-
-
-# TODO: Add BibTeX citation
-# Find for instance the citation on arxiv or on the dataset repo/website
-_CITATION = """\
-@misc{mccreery2020effective,
-      title={Effective Transfer Learning for Identifying Similar Questions: Matching User Questions to COVID-19 FAQs},
-      author={Clara H. McCreery and Namit Katariya and Anitha Kannan and Manish Chablani and Xavier Amatriain},
-      year={2020},
-      eprint={2008.13546},
-      archivePrefix={arXiv},
-      primaryClass={cs.IR}
-}
-"""
-
-
-_DESCRIPTION = """\
-This dataset consists of 3048 similar and dissimilar medical question pairs hand-generated and labeled by Curai's doctors.
-"""
-
-_HOMEPAGE = "https://github.com/curai/medical-question-pair-dataset"
-
-_LICENSE = ""
-
-
-_URL = "https://raw.githubusercontent.com/curai/medical-question-pair-dataset/master/mqp.csv"
-
-
-class MedicalQuestionsPairs(datasets.GeneratorBasedBuilder):
-    """Medical Question Pairs (MQP) Dataset"""
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "dr_id": datasets.Value("int32"),
-                "question_1": datasets.Value("string"),
-                "question_2": datasets.Value("string"),
-                "label": datasets.features.ClassLabel(num_classes=2, names=[0, 1]),
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        data_file = dl_manager.download_and_extract(_URL)
-        return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_file})]
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        with open(filepath, encoding="utf-8") as f:
-            data = csv.reader(f)
-            for id_, row in enumerate(data):
-                yield id_, {
-                    "dr_id": row[0],
-                    "question_1": row[1],
-                    "question_2": row[2],
-                    "label": row[3],
-                }