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 @@
-{"default": {"description": "Snips' built in intents dataset was initially used to compare different voice assistants and released as a public dataset hosted at\nhttps://github.com/sonos/nlu-benchmark 2016-12-built-in-intents. The dataset contains 328 utterances over 10 intent classes. The\nrelated paper mentioned on the github page is https://arxiv.org/abs/1805.10190 and a related Medium post is\nhttps://medium.com/snips-ai/benchmarking-natural-language-understanding-systems-d35be6ce568d .\n", "citation": "@article{DBLP:journals/corr/abs-1805-10190,\n  author    = {Alice Coucke and\n               Alaa Saade and\n               Adrien Ball and\n               Th{'{e}}odore Bluche and\n               Alexandre Caulier and\n               David Leroy and\n               Cl{'{e}}ment Doumouro and\n               Thibault Gisselbrecht and\n               Francesco Caltagirone and\n               Thibaut Lavril and\n               Ma{\"{e}}l Primet and\n               Joseph Dureau},\n  title     = {Snips Voice Platform: an embedded Spoken Language Understanding system\n               for private-by-design voice interfaces},\n  journal   = {CoRR},\n  volume    = {abs/1805.10190},\n  year      = {2018},\n  url       = {http://arxiv.org/abs/1805.10190},\n  archivePrefix = {arXiv},\n  eprint    = {1805.10190},\n  timestamp = {Mon, 13 Aug 2018 16:46:59 +0200},\n  biburl    = {https://dblp.org/rec/journals/corr/abs-1805-10190.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n", "homepage": "https://github.com/sonos/nlu-benchmark/tree/master/2016-12-built-in-intents", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 10, "names": ["ComparePlaces", "RequestRide", "GetWeather", "SearchPlace", "GetPlaceDetails", "ShareCurrentLocation", "GetTrafficInformation", "BookRestaurant", "GetDirections", "ShareETA"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "snips_built_in_intents", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 19431, "num_examples": 328, "dataset_name": "snips_built_in_intents"}}, "download_checksums": {"https://raw.githubusercontent.com/sonos/nlu-benchmark/master/2016-12-built-in-intents/benchmark_data.json": {"num_bytes": 9130264, "checksum": "e3f6ba7b7ab0e8d1a5959a8c8ecb4fc566a281f4ebd34fdf1160929c630d299f"}}, "download_size": 9130264, "post_processing_size": null, "dataset_size": 19431, "size_in_bytes": 9149695}}
+{"default": {"description": "Snips' built in intents dataset was initially used to compare different voice assistants and released as a public dataset hosted at\nhttps://github.com/sonos/nlu-benchmark 2016-12-built-in-intents. The dataset contains 328 utterances over 10 intent classes. The\nrelated paper mentioned on the github page is https://arxiv.org/abs/1805.10190 and a related Medium post is\nhttps://medium.com/snips-ai/benchmarking-natural-language-understanding-systems-d35be6ce568d .\n", "citation": "@article{DBLP:journals/corr/abs-1805-10190,\n  author    = {Alice Coucke and\n               Alaa Saade and\n               Adrien Ball and\n               Th{'{e}}odore Bluche and\n               Alexandre Caulier and\n               David Leroy and\n               Cl{'{e}}ment Doumouro and\n               Thibault Gisselbrecht and\n               Francesco Caltagirone and\n               Thibaut Lavril and\n               Ma{\"{e}}l Primet and\n               Joseph Dureau},\n  title     = {Snips Voice Platform: an embedded Spoken Language Understanding system\n               for private-by-design voice interfaces},\n  journal   = {CoRR},\n  volume    = {abs/1805.10190},\n  year      = {2018},\n  url       = {http://arxiv.org/abs/1805.10190},\n  archivePrefix = {arXiv},\n  eprint    = {1805.10190},\n  timestamp = {Mon, 13 Aug 2018 16:46:59 +0200},\n  biburl    = {https://dblp.org/rec/journals/corr/abs-1805-10190.bib},\n  bibsource = {dblp computer science bibliography, https://dblp.org}\n}\n", "homepage": "https://github.com/sonos/nlu-benchmark/tree/master/2016-12-built-in-intents", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 10, "names": ["ComparePlaces", "RequestRide", "GetWeather", "SearchPlace", "GetPlaceDetails", "ShareCurrentLocation", "GetTrafficInformation", "BookRestaurant", "GetDirections", "ShareETA"], "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": ["BookRestaurant", "ComparePlaces", "GetDirections", "GetPlaceDetails", "GetTrafficInformation", "GetWeather", "RequestRide", "SearchPlace", "ShareCurrentLocation", "ShareETA"]}], "builder_name": "snips_built_in_intents", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 19431, "num_examples": 328, "dataset_name": "snips_built_in_intents"}}, "download_checksums": {"https://raw.githubusercontent.com/sonos/nlu-benchmark/master/2016-12-built-in-intents/benchmark_data.json": {"num_bytes": 9130264, "checksum": "e3f6ba7b7ab0e8d1a5959a8c8ecb4fc566a281f4ebd34fdf1160929c630d299f"}}, "download_size": 9130264, "post_processing_size": null, "dataset_size": 19431, "size_in_bytes": 9149695}}

snips_built_in_intents.py

@@ -20,6 +20,7 @@
 import json
 
 import datasets
+from datasets.tasks import TextClassification
 
 
 _DESCRIPTION = """\
@@ -91,6 +92,7 @@ class SnipsBuiltInIntents(datasets.GeneratorBasedBuilder):
             ),
             homepage="https://github.com/sonos/nlu-benchmark/tree/master/2016-12-built-in-intents",
             citation=_CITATION,
+            task_templates=[TextClassification(text_column="text", label_column="label")],
         )
 
     def _split_generators(self, dl_manager):