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OLD/PAWS-ca.py

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+# Loading script for the PAWS-ca dataset
+import json
+
+import datasets
+
+
+_CITATION = """
+"""
+
+_DESCRIPTION = """
+The PAWS-ca dataset (Paraphrase Adversaries from Word Scrambling in Catalan) is a translation of the English PAWS dataset into Catalan, commissioned by BSC LangTech Unit.
+
+This dataset contains 4,000 human translated PAWS pairs and 49,000 machine translated pairs.
+
+"""
+
+_HOMEPAGE = "https://zenodo.org/record/"
+
+_URL = "https://huggingface.co/datasets/projecte-aina/paws-ca/resolve/main/"
+_TRAIN_FILE = "train.json"
+_DEV_FILE = "dev_2k.json"
+_TEST_FILE = "test_2k.json"
+
+
+class PAWSXConfig(datasets.BuilderConfig):
+    """BuilderConfig for PAWSX-ca."""
+
+    def __init__(self, **kwargs):
+        """Constructs a PAWSXConfig.
+        Args:
+            **kwargs: keyword arguments forwarded to super.
+        """
+        super(PAWSXConfig, self).__init__(version=datasets.Version("1.1.0", ""), **kwargs),
+
+
+class PAWSX(datasets.GeneratorBasedBuilder):
+    """PAWS-ca, a Catalan version of PAWS."""
+
+    VERSION = datasets.Version("1.1.0")
+
+    BUILDER_CONFIGS = [
+        PAWSXConfig(
+            name="paws-ca",
+            description="PAWS-ca dataset",
+        ),
+    ]
+
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "id": datasets.Value("int32"),
+                "sentence1": datasets.Value("string"),
+                "sentence2": datasets.Value("string"),
+                "label": datasets.features.ClassLabel(names=["0", "1"]),
+            }
+        )
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # This defines the different columns of the dataset and their types
+            features=features,  # Here we define them above because they are different between the two configurations
+            # 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=_HOMEPAGE,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        urls_to_download = {
+            "train": f"{_URL}{_TRAIN_FILE}",
+            "dev": f"{_URL}{_DEV_FILE}",
+            "test": f"{_URL}{_TEST_FILE}",
+        }
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding='utf-8') as f:
+            data = json.load(f)
+            for i, row in enumerate(data):
+                yield i, {
+                    'id': row['id'],
+                    'sentence1': row['sentence1'],
+                    'sentence2': row['sentence2'],
+                    'label': row['label'],
+                }
+
+    

OLD/train.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7c504c5b9c2d358575bd711c043326910b0c34fc490ab0fcbce46fe2e18cb6ad
+size 17291348