Upload 3 files

ko-lima.py

@@ -0,0 +1,114 @@
+# 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 = ""
+_URLS = {
+ "plain": "lima_deepl_ko.zip",
+ "vicuna": "lima_deepl_ko_vicuna.zip",
+}
+
+
+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):
+ urls = _URLS[self.config.name]
+ data_dir = dl_manager.download_and_extract(urls)
+ return [
+ datasets.SplitGenerator(
+ name=datasets.Split.TRAIN,
+ gen_kwargs={
+ "filepath": os.path.join(data_dir, "train.jsonl"),
+ "split": "train",
+ },
+ ),
+ # datasets.SplitGenerator(
+ # name=datasets.Split.VALIDATION,
+ # gen_kwargs={
+ # "filepath": os.path.join(data_dir, "dev.jsonl"),
+ # "split": "dev",
+ # },
+ # ),
+ datasets.SplitGenerator(
+ name=datasets.Split.TEST,
+ # These kwargs will be passed to _generate_examples
+ gen_kwargs={
+ "filepath": os.path.join(data_dir, "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

lima_deepl_ko.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7a2c7fb539fc66d0387e5fa9afc88ba705d8a0cb0bc18b02a4df45d2dfaff46d
+size 1154251

lima_deepl_ko_vicuna.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:799dd5ae4d5283f4f1558d4ba22923513ba47af188ace836855c0b2244ae2c1a
+size 1162689