Delete loading script

danfever.py

@@ -1,119 +0,0 @@
-# coding=utf-8
-# Copyright 2020 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
-"""DanFEVER: A FEVER dataset for Danish"""
-
-import csv
-import os
-
-import datasets
-
-
-logger = datasets.logging.get_logger(__name__)
-
-
-_CITATION = """\
-@inproceedings{norregaard-derczynski-2021-danfever,
-    title = "{D}an{FEVER}: claim verification dataset for {D}anish",
-    author = "N{\o}rregaard, Jeppe  and
-      Derczynski, Leon",
-    booktitle = "Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)",
-    month = may # " 31--2 " # jun,
-    year = "2021",
-    address = "Reykjavik, Iceland (Online)",
-    publisher = {Link{\"o}ping University Electronic Press, Sweden},
-    url = "https://aclanthology.org/2021.nodalida-main.47",
-    pages = "422--428",
-    abstract = "We present a dataset, DanFEVER, intended for multilingual misinformation research. The dataset is in Danish and has the same format as the well-known English FEVER dataset. It can be used for testing methods in multilingual settings, as well as for creating models in production for the Danish language.",
-}
-"""
-
-_DESCRIPTION = """\
-
-"""
-
-_URL = "https://media.githubusercontent.com/media/StrombergNLP/danfever/main/tsv/da_fever.tsv"
-
-
-class DanFeverConfig(datasets.BuilderConfig):
-    """BuilderConfig for DanFever"""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig DanFever.
-
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(DanFeverConfig, self).__init__(**kwargs)
-
-
-class DanFever(datasets.GeneratorBasedBuilder):
-    """DanFever dataset."""
-
-    BUILDER_CONFIGS = [
-        DanFeverConfig(name="DanFever", version=datasets.Version("1.0.0"), description="FEVER dataset for Danish"),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "claim": datasets.Value("string"),
-                    "label": datasets.features.ClassLabel(
-                        names=[
-                            "Refuted",
-                            "Supported",
-                            "NotEnoughInfo",
-                        ]
-                    ),
-                    "evidence_extract": datasets.Value("string"),
-                    "verifiable": datasets.features.ClassLabel(
-                        names=[
-                            "NotVerifiable",
-                            "Verifiable",
-                        ]
-                    ),
-                    "evidence": datasets.Value("string"),
-                    "original_id": datasets.Value("string"),
-
-                }
-            ),
-            supervised_keys=None,
-            homepage="https://stromberg.ai/publication/danfever/",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        downloaded_file = dl_manager.download_and_extract(_URL)
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_file}),
-        ]
-
-    def _generate_examples(self, filepath):
-        logger.info("⏳ Generating examples from = %s", filepath)
-        with open(filepath, encoding="utf-8") as f:
-            data_reader = csv.DictReader(f, delimiter="\t", quotechar='"')
-            guid = 0
-            for instance in data_reader:
-                instance.pop('nr.')
-                instance["original_id"] = instance.pop('id')
-                instance["id"] = str(guid)
-                yield guid, instance
-                guid += 1