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

allocine.py

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+"""Allocine Dataset: A Large-Scale French Movie Reviews Dataset."""
+
+from __future__ import absolute_import, division, print_function
+
+import json
+import os
+
+import datasets
+
+
+_CITATION = """\
+@misc{blard2019allocine,
+  author = {Blard, Theophile},
+  title = {french-sentiment-analysis-with-bert},
+  year = {2020},
+  publisher = {GitHub},
+  journal = {GitHub repository},
+  howpublished={\\url{https://github.com/TheophileBlard/french-sentiment-analysis-with-bert}},
+}
+"""
+
+_DESCRIPTION = """\
+ Allocine Dataset: A Large-Scale French Movie Reviews Dataset.
+ This is a dataset for binary sentiment classification, made of user reviews scraped from Allocine.fr.
+ It contains 100k positive and 100k negative reviews divided into 3 balanced splits: train (160k reviews), val (20k) and test (20k).
+"""
+
+
+class AllocineConfig(datasets.BuilderConfig):
+    """BuilderConfig for Allocine."""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for Allocine.
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(AllocineConfig, self).__init__(**kwargs)
+
+
+class AllocineDataset(datasets.GeneratorBasedBuilder):
+    """Allocine Dataset: A Large-Scale French Movie Reviews Dataset."""
+
+    _DOWNLOAD_URL = "https://github.com/TheophileBlard/french-sentiment-analysis-with-bert/raw/master/allocine_dataset/data.tar.bz2"
+    _TRAIN_FILE = "train.jsonl"
+    _VAL_FILE = "val.jsonl"
+    _TEST_FILE = "test.jsonl"
+
+    BUILDER_CONFIGS = [
+        AllocineConfig(
+            name="allocine",
+            version=datasets.Version("1.0.0"),
+            description="Allocine Dataset: A Large-Scale French Movie Reviews Dataset",
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "review": datasets.Value("string"),
+                    "label": datasets.features.ClassLabel(names=["neg", "pos"]),
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://github.com/TheophileBlard/french-sentiment-analysis-with-bert",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        arch_path = dl_manager.download_and_extract(self._DOWNLOAD_URL)
+        data_dir = os.path.join(arch_path, "data")
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(data_dir, self._TRAIN_FILE)}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION, gen_kwargs={"filepath": os.path.join(data_dir, self._VAL_FILE)}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST, gen_kwargs={"filepath": os.path.join(data_dir, self._TEST_FILE)}
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """Generate Allocine examples."""
+        with open(filepath, encoding="utf-8") as f:
+            for id_, row in enumerate(f):
+                data = json.loads(row)
+                review = data["review"]
+                label = "neg" if data["polarity"] == 0 else "pos"
+                yield id_, {"review": review, "label": label}

dataset_infos.json

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+{"allocine": {"description": " Allocine Dataset: A Large-Scale French Movie Reviews Dataset.\n This is a dataset for binary sentiment classification, made of user reviews scraped from Allocine.fr.\n It contains 100k positive and 100k negative reviews divided into 3 balanced splits: train (160k reviews), val (20k) and test (20k).\n", "citation": "@misc{blard2019allocine,\n  author = {Blard, Theophile},\n  title = {french-sentiment-analysis-with-bert},\n  year = {2020},\n  publisher = {GitHub},\n  journal = {GitHub repository},\n  howpublished={\\url{https://github.com/TheophileBlard/french-sentiment-analysis-with-bert}},\n}\n", "homepage": "https://github.com/TheophileBlard/french-sentiment-analysis-with-bert", "license": "", "features": {"review": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["neg", "pos"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "supervised_keys": null, "builder_name": "allocine_dataset", "config_name": "allocine", "version": {"version_str": "1.0.0", "description": null, "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 91330696, "num_examples": 160000, "dataset_name": "allocine_dataset"}, "validation": {"name": "validation", "num_bytes": 11546250, "num_examples": 20000, "dataset_name": "allocine_dataset"}, "test": {"name": "test", "num_bytes": 11547697, "num_examples": 20000, "dataset_name": "allocine_dataset"}}, "download_checksums": {"https://github.com/TheophileBlard/french-sentiment-analysis-with-bert/raw/master/allocine_dataset/data.tar.bz2": {"num_bytes": 66625305, "checksum": "8c49a8cac783da201697ed1a91b36d2f6618222b3b7ea1c2996f2a3fbc37dfb4"}}, "download_size": 66625305, "dataset_size": 114424643, "size_in_bytes": 181049948}}

dummy/allocine/1.0.0/dummy_data.zip

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+size 4367