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@@ -52,3 +52,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+data/original_4096.jsonl filter=lfs diff=lfs merge=lfs -text
+data/original_512.jsonl filter=lfs diff=lfs merge=lfs -text
+data/paraphrased_4096.jsonl filter=lfs diff=lfs merge=lfs -text
+data/paraphrased_512.jsonl filter=lfs diff=lfs merge=lfs -text

data/original_4096.jsonl

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+size 811127234

data/original_512.jsonl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5485019889c5bbcaf38a571bf1680d81a2bb03376b5689d0223dc578d3eb4c4e
+size 829447436

data/paraphrased_4096.jsonl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:bf17100dcc1e4d1daaa3edd157a3c1e3b828594d64a9253f9007e8523234e721
+size 558188350

data/paraphrased_512.jsonl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5485019889c5bbcaf38a571bf1680d81a2bb03376b5689d0223dc578d3eb4c4e
+size 829447436

wikipedia-for-mask-filling.py

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+# dataset loading script for huggingface
+import datasets
+import json
+try:
+    import lzma as xz
+except ImportError:
+    import pylzma as xz
+
+datasets.logging.set_verbosity_info()
+logger = datasets.logging.get_logger(__name__)
+
+_DESCRIPTION = """\
+    """
+
+_HOMEPAGE = "https://skatinger.github.io/master_thesis/",
+
+_LICENSE = ""
+
+_CITATION = ""
+
+_TYPES = ["original", "paraphrased"]
+
+_SIZES = [4096, 512]
+
+_URLS = {
+    "original_4096": "data/original_4096.jsonl.xz",
+    "original_512": "data/original_512.jsonl.xz",
+    "paraphrased_4096": "data/paraphrased_4096.jsonl.xz",
+    "paraphrased_512": "data/paraphrased_512.jsonl.xz"
+}
+
+
+class WikipediaForMaskFillingConfig(datasets.BuilderConfig):
+    """BuilderConfig for WikipediaForMaskFilling.
+
+    features: *list[string]*, list of the features that will appear in the
+    feature dict. Should not include "label".
+    **kwargs: keyword arguments forwarded to super
+    """
+
+    def __init__(self, type, size=4096, **kwargs):
+        """BuilderConfig for WikipediaForMaskFilling.
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+
+        # Version history:
+        # 1.0.0: first version
+        super().__init__(**kwargs)
+        self.size = size
+        self.type = type
+
+
+class WikipediaForMaskFilling(datasets.GeneratorBasedBuilder):
+    """WikipediaForMaskFilling dataset."""
+
+    BUILDER_CONFIGS = [
+        WikipediaForMaskFillingConfig(
+            name="original_4096",
+            version=datasets.Version("1.0.0"),
+            description="Part of the dataset with original texts and masks, with text chunks split into size of max 4096 tokens (Longformer).",
+            max_tokens=4096,
+            type="original"
+        ),
+        WikipediaForMaskFillingConfig(
+            name="original_512",
+            version=datasets.Version("1.0.0"),
+            description="text chunks split into size of max 512 tokens (roberta).",
+            max_tokens=512,
+            type="original"
+        ),
+        WikipediaForMaskFillingConfig(
+            name="paraphrased_4096",
+            version=datasets.Version("1.0.0"),
+            description="Part of the dataset with paraphrased texts and masks, with text chunks split into size of max 4096 tokens (Longformer).",
+            max_tokens=4096,
+            type="paraphrased"
+        ),
+        WikipediaForMaskFillingConfig(
+            name="paraphrased_512",
+            version=datasets.Version("1.0.0"),
+            description="Paraphrased text chunks split into size of max 512 tokens (roberta).",
+            max_tokens=512,
+            type="paraphrased"
+        )
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "texts": datasets.Value("string"),
+                    "masks": datasets.Sequence(datasets.Value("string")),
+                }
+            ),
+            # No default supervised_keys (as we have to pass both question
+            # and context as input).
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        type = self.config.type
+        size = self.config.size
+        urls_to_download = f"data/{type}_{size}.jsonl.xz"
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        _id = 0
+        with open(filepath, encoding="utf-8") as f:
+            try:
+                with xz.open(filepath) as f:
+                    for line in f:
+                        data = json.loads(line)
+                        yield _id, {
+                            "texts": data["texts"],
+                            "masks": data["masks"]
+                        }
+                        _id += 1
+            except Exception:
+                logger.exception("Error while processing file %s", filepath)