Delete ko-lima.py

ko-lima.py

@@ -1,68 +0,0 @@
-import json
-import datasets
-
-# TODO: Add description of the dataset here
-# You can copy an official description
-_DESCRIPTION = """\
-A high-quality dataset for efficient instruction tuning.
-"""
-
-# TODO: Add a link to an official homepage for the dataset here
-_HOMEPAGE = ""
-
-# TODO: Add the licence for the dataset here if you can find it
-_LICENSE = "other"
-
-# TODO: Add link to the official dataset URLs here
-# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
-# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
-_URLS = {
-}
-
-
-class LimaConfig(datasets.BuilderConfig):
-    """BuilderConfig"""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(LimaConfig, self).__init__(**kwargs)
-
-
-class Lima(datasets.GeneratorBasedBuilder):
-
-    BUILDER_CONFIGS = [
-        LimaConfig(
-            name="plain_text",
-            version=datasets.Version("0.0.1", ""),
-            description="Plain text",
-        ),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "conversations": datasets.features.Sequence(datasets.Value("string")),
-                    "source": datasets.Value("string"),
-                }
-            ),
-        )
-
-    def _split_generators(self, dl_manager):
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": dl_manager.download("lima_train_deepl_ko.jsonl")}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath":dl_manager.download("lima_test_deepl_ko.jsonl")})
-        ]
-
-    def _generate_examples(self, filepath):
-        """This function returns the examples in the raw (text) form."""
-        key = 0
-        with open(filepath) as f:
-            for line in f.readlines():
-                instance = json.loads(line)
-                yield key, instance
-                key += 1