Delete ko-lima.py

ko-lima.py

@@ -1,102 +0,0 @@
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import csv
-import json
-import os
-import datasets
-
-
-_CITATION = """\
-@InProceedings{huggingface:dataset,
-title = {Ko-LIMA: Korean LIMA Dataset},
-author={Hahn, Taeseung},
-year={2023}
-}
-"""
-_DESCRIPTION = """\
-A high-quality korean dataset for efficient instruction tuning.
-"""
-_HOMEPAGE = ""
-_LICENSE = ""
-
-
-class KoLima(datasets.GeneratorBasedBuilder):
-    """A high-quality korean dataset for efficient instruction tuning."""
-
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="plain", version=VERSION, description="Korean LIMA dataset in a plain format"),
-        datasets.BuilderConfig(name="vicuna", version=VERSION, description="Korean LIMA dataset in Vicuna format"),
-    ]
-
-    DEFAULT_CONFIG_NAME = "plain"
-
-    def _info(self):
-        if self.config.name == "vicuna":
-            features = datasets.Features(
-                {
-                    'id': datasets.Value(dtype='string', id=None),
-                    'conversations': [
-                        {
-                            'from': datasets.Value(dtype='string', id=None),
-                            'value': datasets.Value(dtype='string', id=None)
-                        }
-                    ]
-                }
-            )
-        else:
-            features = datasets.Features(
-                {
-                    'conversations': datasets.Sequence(feature=datasets.Value(dtype='string', id=None), length=-1, id=None),
-                    'source': datasets.Value(dtype='string', id=None)
-                }
-            )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": dl_manager.download(os.path.join(self.config.name, "train.jsonl")),
-                    "split": "train",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": dl_manager.download(os.path.join(self.config.name, "test.jsonl")),
-                    "split": "test"
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath, split):
-        with open(filepath, encoding="utf-8") as f:
-            for key, row in enumerate(f):
-                instance = json.loads(row)
-                if self.config.name == "vicuna":
-                    yield key, instance
-                else:
-                    yield key, instance