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": "Arabic Poetry Metric Classification.\nThe dataset contains the verses and their corresponding meter classes.Meter classes are represented as numbers from 0 to 13. The dataset can be highly useful for further research in order to improve the field of Arabic poems\u2019 meter classification.The train dataset contains 47,124 records and the test dataset contains 8316 records.\n", "citation": "@article{al2020meter,\n  title={Meter Classification of Arabic Poems Using Deep Bidirectional Recurrent Neural Networks},\n  author={Al-shaibani, Maged S and Alyafeai, Zaid and Ahmad, Irfan},\n  journal={Pattern Recognition Letters},\n  year={2020},\n  publisher={Elsevier}\n}\n", "homepage": "https://github.com/zaidalyafeai/MetRec", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 14, "names": ["saree", "kamel", "mutakareb", "mutadarak", "munsareh", "madeed", "mujtath", "ramal", "baseet", "khafeef", "taweel", "wafer", "hazaj", "rajaz"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "metrec", "config_name": "plain_text", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 5874919, "num_examples": 47124, "dataset_name": "metrec"}, "test": {"name": "test", "num_bytes": 1037577, "num_examples": 8316, "dataset_name": "metrec"}}, "download_checksums": {"https://raw.githubusercontent.com/zaidalyafeai/MetRec/master/baits.zip": {"num_bytes": 2267882, "checksum": "558ac80e54a9111f9d784e898526ce8bc831d06aafd2110cb2acd216a667dbf7"}}, "download_size": 2267882, "post_processing_size": null, "dataset_size": 6912496, "size_in_bytes": 9180378}}
+{"plain_text": {"description": "Arabic Poetry Metric Classification.\nThe dataset contains the verses and their corresponding meter classes.Meter classes are represented as numbers from 0 to 13. The dataset can be highly useful for further research in order to improve the field of Arabic poems\u2019 meter classification.The train dataset contains 47,124 records and the test dataset contains 8316 records.\n", "citation": "@article{metrec2020,\n  title={MetRec: A dataset for meter classification of arabic poetry},\n  author={Al-shaibani, Maged S and Alyafeai, Zaid and Ahmad, Irfan},\n  journal={Data in Brief},\n  year={2020},\n  publisher={Elsevier}\n}\n", "homepage": "https://github.com/zaidalyafeai/MetRec", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 14, "names": ["saree", "kamel", "mutakareb", "mutadarak", "munsareh", "madeed", "mujtath", "ramal", "baseet", "khafeef", "taweel", "wafer", "hazaj", "rajaz"], "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": ["baseet", "hazaj", "kamel", "khafeef", "madeed", "mujtath", "munsareh", "mutadarak", "mutakareb", "rajaz", "ramal", "saree", "taweel", "wafer"]}], "builder_name": "metrec", "config_name": "plain_text", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 5874919, "num_examples": 47124, "dataset_name": "metrec"}, "test": {"name": "test", "num_bytes": 1037577, "num_examples": 8316, "dataset_name": "metrec"}}, "download_checksums": {"https://raw.githubusercontent.com/zaidalyafeai/MetRec/master/baits.zip": {"num_bytes": 2267882, "checksum": "558ac80e54a9111f9d784e898526ce8bc831d06aafd2110cb2acd216a667dbf7"}}, "download_size": 2267882, "post_processing_size": null, "dataset_size": 6912496, "size_in_bytes": 9180378}}

metrec.py

@@ -20,6 +20,7 @@
 import os
 
 import datasets
+from datasets.tasks import TextClassification
 
 
 _DESCRIPTION = """\
@@ -94,6 +95,7 @@ class Metrec(datasets.GeneratorBasedBuilder):
             supervised_keys=None,
             homepage="https://github.com/zaidalyafeai/MetRec",
             citation=_CITATION,
+            task_templates=[TextClassification(text_column="text", label_column="label")],
         )
 
     def _vocab_text_gen(self, archive):