Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

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README.md

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+---
+annotations_creators:
+- found
+language_creators:
+- found
+languages:
+- tr
+licenses:
+- unknown
+multilinguality:
+- monolingual
+size_categories:
+- 100k<n<1M
+source_datasets:
+- original
+task_categories:
+- text_classification
+task_ids:
+- text_classification-other-news-category-classification
+---
+
+# Dataset Card for Interpress Turkish News Category Dataset (270K)
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Discussion of Social Impact and Biases](#discussion-of-social-impact-and-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** [Interpress](https://www.interpress.com/)
+- **Point of Contact:** [Yavuz Komecoglu](mailto:[email protected])
+
+### Dataset Summary
+
+Turkish News Category Dataset (270K) is a Turkish news data set consisting of 273601 news in 17 categories, compiled from printed media and news websites between 2010 and 2017 by the Interpress (https://www.interpress.com/) media monitoring company.
+
+### Languages
+
+The dataset is based on Turkish.
+
+## Dataset Structure
+
+### Data Instances
+
+A text classification dataset with 17 different news category. 
+
+### Data Fields
+
+[More Information Needed]
+
+### Data Splits
+
+The data is split into a training and testing. The split is organized as the following 
+
+|           | Tain    | Test  |
+|---------- | ------- | ----- |
+|data split | 218,880 | 54,721|
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+[More Information Needed]
+
+#### Initial Data Collection and Normalization
+
+Downloaded over 270,000 news from the printed media and news websites between 2010 and 2017 by the Interpress (https://www.interpress.com/) media monitoring company. This data collection compiled from print media and internet news is presented in its raw form. For this reason, it is appropriate to use it with careful pre-processing steps regarding various OCR errors and typos.
+
+
+#### Who are the source language producers?
+
+Turkish printed news sources and online news sites. 
+
+### Annotations
+
+The dataset does not contain any additional annotations.
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Discussion of Social Impact and Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]

dataset_infos.json

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+{"270k": {"description": "It is a Turkish news data set consisting of 273601 news in 17 categories, compiled from print media and news websites between 2010 and 2017 by the Interpress (https://www.interpress.com/) media monitoring company.\n", "citation": "", "homepage": "https://www.interpress.com/", "license": "", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "content": {"dtype": "string", "id": null, "_type": "Value"}, "category": {"num_classes": 17, "names": ["aktuel", "bilisim", "egitim", "ekonomi", "gida", "iletisim", "kultursanat", "magazin", "saglik", "savunma", "seyahat", "siyasi", "spor", "teknoloji", "ticaret", "turizm", "yasam"], "names_file": null, "id": null, "_type": "ClassLabel"}, "categorycode": {"num_classes": 17, "names": ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16"], "names_file": null, "id": null, "_type": "ClassLabel"}, "publishdatetime": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "interpress_news_category_tr", "config_name": "270k", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 736098052, "num_examples": 218880, "dataset_name": "interpress_news_category_tr"}, "test": {"name": "test", "num_bytes": 184683629, "num_examples": 54721, "dataset_name": "interpress_news_category_tr"}}, "download_checksums": {"https://www.interpress.com/downloads/interpress_news_category_tr_270k.zip": {"num_bytes": 354802486, "checksum": "f41659ed1f38e36759e382eaef2b6bd3680b3a8d49f4d6ef1829d8d0d999e246"}}, "download_size": 354802486, "post_processing_size": null, "dataset_size": 920781681, "size_in_bytes": 1275584167}}

dummy/270k/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4aecc3f9d12fdcef888c6c93facff8b921fdb732d3a30c886b0ce1c47f90e578
+size 10025

interpress_news_category_tr.py

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+# 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.
+# Lint as: python3
+"""Turkish News Category Dataset (270K) - Interpress Media Monitoring Company"""
+
+from __future__ import absolute_import, division, print_function
+
+import csv
+import logging
+import os
+
+import datasets
+
+
+_DESCRIPTION = """\
+It is a Turkish news data set consisting of 273601 news in 17 categories, compiled from print media and news websites between 2010 and 2017 by the Interpress (https://www.interpress.com/) media monitoring company.
+"""
+
+_CITATION = ""
+_LICENSE = "unknown"
+_HOMEPAGE = "https://www.interpress.com/"
+_DOWNLOAD_URL = "https://www.interpress.com/downloads/interpress_news_category_tr_270k.zip"
+_DATASET_URLS = {
+    "train": "interpress_news_category_tr_270k_train.tsv",
+    "test": "interpress_news_category_tr_270k_test.tsv",
+}
+
+
+class InterpressNewsCategoryTRConfig(datasets.BuilderConfig):
+    """BuilderConfig for InterpressNewsCategoryTR."""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for InterpressNewsCategoryTR.
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(InterpressNewsCategoryTRConfig, self).__init__(**kwargs)
+
+
+class InterpressNewsCategoryTR(datasets.GeneratorBasedBuilder):
+    """Turkish News Category Dataset (270K) - Interpress Media Monitoring Company"""
+
+    BUILDER_CONFIGS = [
+        InterpressNewsCategoryTRConfig(
+            name="270k",
+            version=datasets.Version("1.0.0"),
+            description="Turkish News Category Dataset (270K) - Interpress Media Monitoring Company",
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("int32"),
+                    "title": datasets.Value("string"),
+                    "content": datasets.Value("string"),
+                    "category": datasets.features.ClassLabel(
+                        names=[
+                            "aktuel",
+                            "bilisim",
+                            "egitim",
+                            "ekonomi",
+                            "gida",
+                            "iletisim",
+                            "kultursanat",
+                            "magazin",
+                            "saglik",
+                            "savunma",
+                            "seyahat",
+                            "siyasi",
+                            "spor",
+                            "teknoloji",
+                            "ticaret",
+                            "turizm",
+                            "yasam",
+                        ]
+                    ),
+                    "categorycode": datasets.features.ClassLabel(num_classes=17),
+                    "publishdatetime": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        dl_dir = dl_manager.download_and_extract(_DOWNLOAD_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(dl_dir, _DATASET_URLS["train"])}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST, gen_kwargs={"filepath": os.path.join(dl_dir, _DATASET_URLS["test"])}
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """Generate InterpressNewsCategoryTR examples."""
+        logging.info("⏳ Generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as f:
+            reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
+            for idx, row in enumerate(reader):
+                yield idx, {
+                    "id": row["ID"],
+                    "title": row["Title"],
+                    "content": row["Content"],
+                    "category": row["Category"],
+                    "categorycode": row["CategoryCode"],
+                    "publishdatetime": row["PublishDateTime"],
+                }