Delete loading script

hate_speech_offensive.py

@@ -1,105 +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.
-"""An annotated dataset for hate speech and offensive language detection on tweets."""
-
-
-import csv
-
-import datasets
-
-
-_CITATION = """\
-@inproceedings{hateoffensive,
-title = {Automated Hate Speech Detection and the Problem of Offensive Language},
-author = {Davidson, Thomas and Warmsley, Dana and Macy, Michael and Weber, Ingmar},
-booktitle = {Proceedings of the 11th International AAAI Conference on Web and Social Media},
-series = {ICWSM '17},
-year = {2017},
-location = {Montreal, Canada},
-pages = {512-515}
-}
-"""
-
-_DESCRIPTION = """\
-An annotated dataset for hate speech and offensive language detection on tweets.
-"""
-
-_HOMEPAGE = "https://github.com/t-davidson/hate-speech-and-offensive-language"
-
-_LICENSE = "MIT"
-
-_URL = "https://raw.githubusercontent.com/t-davidson/hate-speech-and-offensive-language/master/data/labeled_data.csv"
-
-_CLASS_MAP = {
-    "0": "hate speech",
-    "1": "offensive language",
-    "2": "neither",
-}
-
-
-class HateSpeechOffensive(datasets.GeneratorBasedBuilder):
-    """An annotated dataset for hate speech and offensive language detection on tweets."""
-
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "count": datasets.Value("int64"),
-                    "hate_speech_count": datasets.Value("int64"),
-                    "offensive_language_count": datasets.Value("int64"),
-                    "neither_count": datasets.Value("int64"),
-                    "class": datasets.ClassLabel(names=["hate speech", "offensive language", "neither"]),
-                    "tweet": datasets.Value("string"),
-                }
-            ),
-            supervised_keys=("tweet", "class"),
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-
-        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:
-            reader = csv.reader(f)
-            for id_, row in enumerate(reader):
-                if id_ == 0:
-                    continue
-
-                yield id_, {
-                    "count": row[1],
-                    "hate_speech_count": row[2],
-                    "offensive_language_count": row[3],
-                    "neither_count": row[4],
-                    "class": _CLASS_MAP[row[5]],
-                    "tweet": row[6],
-                }