Update files from the datasets library (from 1.8.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.8.0

dataset_infos.json

@@ -1 +1 @@
-{"plain_text": {"description": "The Dutch Book Review Dataset (DBRD) contains over 110k book reviews of which 22k have associated binary sentiment polarity labels. It is intended as a benchmark for sentiment classification in Dutch and created due to a lack of annotated datasets in Dutch that are suitable for this task.\n", "citation": "@article{DBLP:journals/corr/abs-1910-00896,\n  author    = {Benjamin van der Burgh and\n               Suzan Verberne},\n  title     = {The merits of Universal Language Model Fine-tuning for Small Datasets\n               - a case with Dutch book reviews},\n  journal   = {CoRR},\n  volume    = {abs/1910.00896},\n  year      = {2019},\n  url       = {http://arxiv.org/abs/1910.00896},\n  archivePrefix = {arXiv},\n  eprint    = {1910.00896},\n  timestamp = {Fri, 04 Oct 2019 12:28:06 +0200},\n  biburl    = {https://dblp.org/rec/journals/corr/abs-1910-00896.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n", "homepage": "https://github.com/benjaminvdb/DBRD", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["neg", "pos"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "dbrd", "config_name": "plain_text", "version": {"version_str": "3.0.0", "description": "", "major": 3, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 29496333, "num_examples": 20028, "dataset_name": "dbrd"}, "test": {"name": "test", "num_bytes": 3246243, "num_examples": 2224, "dataset_name": "dbrd"}, "unsupervised": {"name": "unsupervised", "num_bytes": 152733031, "num_examples": 96264, "dataset_name": "dbrd"}}, "download_checksums": {"https://github.com/benjaminvdb/DBRD/releases/download/v3.0/DBRD_v3.tgz": {"num_bytes": 79065872, "checksum": "2d7eed5a2c56b19fec22f1656722b6036569aa542d362e576bd761eb91e1e76a"}}, "download_size": 79065872, "post_processing_size": null, "dataset_size": 185475607, "size_in_bytes": 264541479}}
+{"plain_text": {"description": "The Dutch Book Review Dataset (DBRD) contains over 110k book reviews of which 22k have associated binary sentiment polarity labels. It is intended as a benchmark for sentiment classification in Dutch and created due to a lack of annotated datasets in Dutch that are suitable for this task.\n", "citation": "@article{DBLP:journals/corr/abs-1910-00896,\n  author    = {Benjamin van der Burgh and\n               Suzan Verberne},\n  title     = {The merits of Universal Language Model Fine-tuning for Small Datasets\n               - a case with Dutch book reviews},\n  journal   = {CoRR},\n  volume    = {abs/1910.00896},\n  year      = {2019},\n  url       = {http://arxiv.org/abs/1910.00896},\n  archivePrefix = {arXiv},\n  eprint    = {1910.00896},\n  timestamp = {Fri, 04 Oct 2019 12:28:06 +0200},\n  biburl    = {https://dblp.org/rec/journals/corr/abs-1910-00896.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n", "homepage": "https://github.com/benjaminvdb/DBRD", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["neg", "pos"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "text-classification", "text_column": "text", "label_column": "label", "labels": ["neg", "pos"]}], "builder_name": "dbrd", "config_name": "plain_text", "version": {"version_str": "3.0.0", "description": "", "major": 3, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 29496333, "num_examples": 20028, "dataset_name": "dbrd"}, "test": {"name": "test", "num_bytes": 3246243, "num_examples": 2224, "dataset_name": "dbrd"}, "unsupervised": {"name": "unsupervised", "num_bytes": 152733031, "num_examples": 96264, "dataset_name": "dbrd"}}, "download_checksums": {"https://github.com/benjaminvdb/DBRD/releases/download/v3.0/DBRD_v3.tgz": {"num_bytes": 79065872, "checksum": "2d7eed5a2c56b19fec22f1656722b6036569aa542d362e576bd761eb91e1e76a"}}, "download_size": 79065872, "post_processing_size": null, "dataset_size": 185475607, "size_in_bytes": 264541479}}

dbrd.py

@@ -20,6 +20,7 @@
 import os
 
 import datasets
+from datasets.tasks import TextClassification
 
 
 _DESCRIPTION = """\
@@ -81,6 +82,7 @@ class DBRD(datasets.GeneratorBasedBuilder):
             supervised_keys=None,
             homepage="https://github.com/benjaminvdb/DBRD",
             citation=_CITATION,
+            task_templates=[TextClassification(text_column="text", label_column="label")],
         )
 
     def _vocab_text_gen(self, archive):