Initial commit

.gitattributes

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README.md

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+---
+dataset_info:
+  features:
+  - name: id
+    dtype: uint64
+  - name: text
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 125126513109
+    num_examples: 223256
+  download_size: 34905399148
+  dataset_size: 125126513109
+---

librusec.py

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+# coding=utf-8
+# Copyright 2023 The HuggingFace Datasets Authors and Ilya Gusev
+#
+# 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.
+
+# Lint as: python3
+import os
+import io
+
+import zstandard
+import jsonlines
+import datasets
+
+try:
+    import simdjson
+    parser = simdjson.Parser()
+    def parse_json(x):
+        try:
+            return parser.parse(x).as_dict()
+        except ValueError:
+            return
+except ImportError:
+    import json
+    def parse_json(x):
+        return json.loads(x)
+
+_DESCRIPTION = "Librusec dataset"
+_TRAIN_SPLITS = 20
+_URLS = ["{}.jsonl.zst".format(str(i).zfill(2)) for i in range(_TRAIN_SPLITS)]
+
+
+class LibrusecDataset(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("0.0.1")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="default", version=VERSION, description=""),
+    ]
+
+    DEFAULT_CONFIG_NAME = "default"
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "id": datasets.Value("uint64"),
+                "text": datasets.Value("string"),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features
+        )
+
+    def _split_generators(self, dl_manager):
+        downloaded_files = dl_manager.download(_URLS)
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"paths": downloaded_files}),
+        ]
+
+    def _generate_examples(self, paths):
+        for path in paths:
+            with open(path, "rb") as f:
+                cctx = zstandard.ZstdDecompressor()
+                reader_stream = io.BufferedReader(cctx.stream_reader(f))
+                reader = jsonlines.Reader(reader_stream, loads=parse_json)
+                for id_, item in enumerate(reader):
+                    yield id_, item