Initial

.gitattributes

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 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+habr.jsonl.zst filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+dataset_info:
+  features:
+  - name: text
+    dtype: string
+  - name: meta
+    struct:
+    - name: id
+      dtype: uint32
+    - name: time_published
+      dtype: uint64
+    - name: title
+      dtype: string
+    - name: author
+      dtype: string
+    - name: statistics
+      struct:
+      - name: commentsCount
+        dtype: uint32
+      - name: favoritesCount
+        dtype: uint32
+      - name: readingCount
+        dtype: uint32
+      - name: score
+        dtype: int32
+      - name: votesCount
+        dtype: int32
+      - name: votesCountPlus
+        dtype: int32
+      - name: votesCountMinus
+        dtype: int32
+  splits:
+  - name: train
+    num_bytes: 3734746780
+    num_examples: 296802
+  download_size: 1084715944
+  dataset_size: 3734746780
+task_categories:
+- text-generation
+language:
+- ru
+---
+
+# Habrahabr dataset

habr.jsonl.zst

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3f0874d5d7e1e4e0932571c4bb4bb776810a50f5eb57fb630849960316b83ccc
+size 1084715944

habr.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
+"""Habrahabr dataset"""
+
+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 = "Habrahabr dataset"
+_URL = "habr.jsonl.zst"
+
+
+class RuLMDataset(datasets.GeneratorBasedBuilder):
+    """Habrahabr dataset"""
+
+    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(
+            {
+                "text": datasets.Value("string"),
+                "meta": {
+                    "id": datasets.Value("uint32"),
+                    "time_published": datasets.Value("uint64"),
+                    "title": datasets.Value("string"),
+                    "author": datasets.Value("string"),
+                    "statistics": {
+                        "commentsCount": datasets.Value("uint32"),
+                        "favoritesCount": datasets.Value("uint32"),
+                        "readingCount": datasets.Value("uint32"),
+                        "score": datasets.Value("int32"),
+                        "votesCount": datasets.Value("int32"),
+                        "votesCountPlus": datasets.Value("int32"),
+                        "votesCountMinus": datasets.Value("int32")
+                    }
+                }
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features
+        )
+
+    def _split_generators(self, dl_manager):
+        downloaded_file = dl_manager.download(_URL)
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"path": downloaded_file}),
+        ]
+
+    def _generate_examples(self, path):
+        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_, {"text": item["text"], "meta": item["meta"]}