Update files from the datasets library (from 1.0.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.0.0

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

dataset_infos.json

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+{"default": {"description": "The x-stance dataset contains more than 150 political questions, and 67k comments written by candidates on those questions.\n\nIt can be used to train and evaluate stance detection systems.\n\n", "citation": "@inproceedings{vamvas2020xstance,\n    author    = \"Vamvas, Jannis and Sennrich, Rico\",\n    title     = \"{X-Stance}: A Multilingual Multi-Target Dataset for Stance Detection\",\n    booktitle = \"Proceedings of the 5th Swiss Text Analytics Conference (SwissText) \\& 16th Conference on Natural Language Processing (KONVENS)\",\n    address   = \"Zurich, Switzerland\",\n    year      = \"2020\",\n    month     = \"jun\",\n    url       = \"http://ceur-ws.org/Vol-2624/paper9.pdf\"\n}\n", "homepage": "https://github.com/ZurichNLP/xstance", "license": "", "features": {"question": {"dtype": "string", "id": null, "_type": "Value"}, "id": {"dtype": "int32", "id": null, "_type": "Value"}, "question_id": {"dtype": "int32", "id": null, "_type": "Value"}, "language": {"dtype": "string", "id": null, "_type": "Value"}, "comment": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}, "numerical_label": {"dtype": "int32", "id": null, "_type": "Value"}, "author": {"dtype": "string", "id": null, "_type": "Value"}, "topic": {"dtype": "string", "id": null, "_type": "Value"}}, "supervised_keys": null, "builder_name": "x_stance", "config_name": "default", "version": {"version_str": "0.1.0", "description": null, "datasets_version_to_prepare": null, "major": 0, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 17619123, "num_examples": 45640, "dataset_name": "x_stance"}, "test": {"name": "test", "num_bytes": 6607134, "num_examples": 17705, "dataset_name": "x_stance"}, "validation": {"name": "validation", "num_bytes": 1505979, "num_examples": 3926, "dataset_name": "x_stance"}}, "download_checksums": {"https://github.com/ZurichNLP/xstance/raw/v1.0.0/data/xstance-data-v1.0.zip": {"num_bytes": 6410801, "checksum": "b8d0168f1897880ccbcb27946e0b2e45de9ac17bc048daad84949fcfe4351768"}}, "download_size": 6410801, "dataset_size": 25732236, "size_in_bytes": 32143037}}

dummy/0.1.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8637809d7a081908d7e394f4acdee2382cb20744370502a3be3b9aaa026243f8
+size 2317

x_stance.py

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+"""TODO(x_stance): Add a description here."""
+
+from __future__ import absolute_import, division, print_function
+
+import json
+import os
+
+import datasets
+
+
+# TODO(x_stance): BibTeX citation
+_CITATION = """\
+@inproceedings{vamvas2020xstance,
+    author    = "Vamvas, Jannis and Sennrich, Rico",
+    title     = "{X-Stance}: A Multilingual Multi-Target Dataset for Stance Detection",
+    booktitle = "Proceedings of the 5th Swiss Text Analytics Conference (SwissText) \\& 16th Conference on Natural Language Processing (KONVENS)",
+    address   = "Zurich, Switzerland",
+    year      = "2020",
+    month     = "jun",
+    url       = "http://ceur-ws.org/Vol-2624/paper9.pdf"
+}
+"""
+
+# TODO(x_stance):
+_DESCRIPTION = """\
+The x-stance dataset contains more than 150 political questions, and 67k comments written by candidates on those questions.
+
+It can be used to train and evaluate stance detection systems.
+
+"""
+
+_URL = "https://github.com/ZurichNLP/xstance/raw/v1.0.0/data/xstance-data-v1.0.zip"
+
+
+class XStance(datasets.GeneratorBasedBuilder):
+    """TODO(x_stance): Short description of my dataset."""
+
+    # TODO(x_stance): Set up version.
+    VERSION = datasets.Version("0.1.0")
+
+    def _info(self):
+        # TODO(x_stance): Specifies the datasets.DatasetInfo object
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # datasets.features.FeatureConnectors
+            features=datasets.Features(
+                {
+                    "question": datasets.Value("string"),
+                    "id": datasets.Value("int32"),
+                    "question_id": datasets.Value("int32"),
+                    "language": datasets.Value("string"),
+                    "comment": datasets.Value("string"),
+                    "label": datasets.Value("string"),
+                    "numerical_label": datasets.Value("int32"),
+                    "author": datasets.Value("string"),
+                    "topic": datasets.Value("string")
+                    # These are the features of your dataset like images, labels ...
+                }
+            ),
+            # If there's a common (input, target) tuple from the features,
+            # specify them here. They'll be used if as_supervised=True in
+            # builder.as_dataset.
+            supervised_keys=None,
+            # Homepage of the dataset for documentation
+            homepage="https://github.com/ZurichNLP/xstance",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        # TODO(x_stance): Downloads the data and defines the splits
+        # dl_manager is a datasets.download.DownloadManager that can be used to
+        # download and extract URLs
+        dl_dir = dl_manager.download_and_extract(_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"filepath": os.path.join(dl_dir, "train.jsonl")},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"filepath": os.path.join(dl_dir, "test.jsonl")},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"filepath": os.path.join(dl_dir, "valid.jsonl")},
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        # TODO(x_stance): Yields (key, example) tuples from the dataset
+        with open(filepath, encoding="utf-8") as f:
+            for id_, row in enumerate(f):
+                data = json.loads(row)
+
+                yield id_, {
+                    "id": data["id"],
+                    "question_id": data["question_id"],
+                    "question": data["question"],
+                    "comment": data["comment"],
+                    "label": data["label"],
+                    "author": data["author"],
+                    "numerical_label": data["numerical_label"],
+                    "topic": data["topic"],
+                    "language": data["language"],
+                }