Delete PAWS-ca.py

PAWS-ca.py

@@ -1,97 +0,0 @@
-# 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'],
-                }
-
-