Update mind.py

mind.py

@@ -1,41 +1,7 @@
-# coding=utf-8
-# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
-#
-# 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.
-
-# Lint as: python3
-"""MIND dataset."""
-
-
 import csv
-
 import datasets
 from datasets.tasks import TextClassification
 
-
-_DESCRIPTION = """\
-MIND
-"""
-
-_CITATION = """\
-@inproceedings{Zhang2015CharacterlevelCN,
-  title={Character-level Convolutional Networks for Text Classification},
-  author={Xiang Zhang and Junbo Jake Zhao and Yann LeCun},
-  booktitle={NIPS},
-  year={2015}
-}
-"""
-
 _TRAIN_DOWNLOAD_URL = "https://huggingface.co/datasets/linxinyuan/mind/resolve/main/train.csv"
 _TEST_DOWNLOAD_URL = "https://huggingface.co/datasets/linxinyuan/mind/resolve/main/test.csv"
 
@@ -45,22 +11,16 @@ class mind(datasets.GeneratorBasedBuilder):
 
     def _info(self):
         return datasets.DatasetInfo(
-            description=_DESCRIPTION,
+            description="MIND",
             features=datasets.Features(
                 {
-                    "NewsID": datasets.Value("string"),
-                    "Category": datasets.features.ClassLabel(names=['foodanddrink', 'games', 'lifestyle', 'weather', 'kids', 'entertainment', 'middleeast', 'news', 'autos', 'video', 'travel', 'music', 'northamerica', 'movies', 'finance', 'health', 'sports', 'tv']),
-                    "SubCategory": datasets.Value("string"),
-                    "Title": datasets.Value("string"),
-                    "Abstract": datasets.Value("string"),
-                    "URL": datasets.Value("string"),
-                    "TitleEntities": datasets.Value("string"),
-                    "AbstractEntites": datasets.Value("string"),
+                    "label": datasets.features.ClassLabel(names=['foodanddrink', 'games', 'lifestyle', 'weather', 'kids', 'entertainment', 'middleeast', 'news', 'autos', 'video', 'travel', 'music', 'northamerica', 'movies', 'finance', 'health', 'sports', 'tv']),
+                    "text": datasets.Value("string")
                 }
             ),
             homepage="http://groups.di.unipi.it/~gulli/AG_corpus_of_news_articles.html",
-            citation=_CITATION,
-            task_templates=[TextClassification(text_column="Title", label_column="Category")],
+            citation="",
+            task_templates=[TextClassification(text_column="text", label_column="label")],
         )
 
     def _split_generators(self, dl_manager):