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  1. README.md +295 -0
  2. arxiv_cs_math/train-00000.jsonl.gz +3 -0
  3. commitpack/train-00000.jsonl.gz +3 -0
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  8. recipe.json +139 -0
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  11. stackexchange_programming/train-00000.jsonl.gz +3 -0
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README.md ADDED
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1
+ ---
2
+ pretty_name: Code Corpus code-v1
3
+ language:
4
+ - code
5
+ - en
6
+ license: other
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+ license_name: mixed-open-licenses
8
+ task_categories:
9
+ - text-generation
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+ size_categories:
11
+ - 1M<n<10M
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+ source_datasets:
13
+ - extended
14
+ annotations_creators:
15
+ - no-annotation
16
+ language_creators:
17
+ - found
18
+ multilinguality:
19
+ - multilingual
20
+ tags:
21
+ - code
22
+ - text
23
+ - datasets
24
+ - pretraining
25
+ - continued-pretraining
26
+ - software-engineering
27
+ configs:
28
+ - config_name: default
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+ default: true
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+ data_files:
31
+ - split: train
32
+ path: "*/*.jsonl.gz"
33
+ ---
34
+
35
+ # Dataset Card for Code Corpus `code-v1`
36
+
37
+ ## Dataset Description
38
+
39
+ ### Dataset Summary
40
+
41
+ Code Corpus `code-v1` is a token-balanced collection of source code, commit messages and
42
+ diffs, programming Q&A, and technical text. It is intended for language-model pretraining
43
+ and continued pretraining. All examples use a common JSONL schema with per-record
44
+ provenance, license metadata, exact token counts, and content hashes.
45
+
46
+ The released dataset contains **2 billion tokens**, **2,541,336 documents**, and **46**
47
+ gzip-compressed shards totaling **2.91 GB** (2,905,546,899 bytes; 2.71 GiB).
48
+ Exact source totals and the complete shard inventory are recorded in
49
+ [`manifest.json`](manifest.json).
50
+
51
+ ### Supported Tasks
52
+
53
+ The dataset is designed for causal language modeling over code and technical text. It is
54
+ not an instruction-tuning dataset and does not include labels, preference pairs, or a
55
+ held-out evaluation split.
56
+
57
+ ### Languages
58
+
59
+ The corpus contains many programming languages and predominantly English natural-language
60
+ content. Other human languages may occur in source comments, commit messages, repository
61
+ content, and upstream technical-text collections. The `language` field describes a
62
+ programming language when upstream metadata is available; it is not a human-language tag.
63
+
64
+ ## Dataset Structure
65
+
66
+ ### Data Instances
67
+
68
+ Each line in a decompressed shard is an independent JSON object:
69
+
70
+ ```json
71
+ {
72
+ "id": "29266961adb8c59a77001330377561454f9d82e5dadfeff7445a14ae147ac453",
73
+ "text": "// source code, technical text, or a commit message and diff",
74
+ "source": "stackv2_edu",
75
+ "source_id": "6396980ea790ba1a35f35ff6269bb0d8d0b58ddf",
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+ "language": "JavaScript",
77
+ "license": "MIT",
78
+ "url": "https://raw.githubusercontent.com/...",
79
+ "repository": "owner/repository",
80
+ "path": "/path/to/file.js",
81
+ "created": "2020-03-02 08:38:22",
82
+ "metadata": {},
83
+ "content_sha256": "72f9484f64be497baa6bd276fbfdbed13e43735445f0aedb635907314d223ceb",
84
+ "chunk_index": 0,
85
+ "token_count": 599
86
+ }
87
+ ```
88
+
89
+ CommitPack examples format `text` as a natural-language commit message followed by a
90
+ unified diff.
91
+
92
+ ### Data Fields
93
+
94
+ | Field | Type | Description |
95
+ | --- | --- | --- |
96
+ | `id` | string | Stable SHA-256 record identifier. |
97
+ | `text` | string | Model training text. |
98
+ | `source` | string | Source name matching a recipe entry and shard directory. |
99
+ | `source_id` | string or null | Upstream example identifier. |
100
+ | `language` | string or null | Upstream or detected programming language. |
101
+ | `license` | string or null | Upstream license label for the example. |
102
+ | `url` | string or null | Original or raw-content URL when available. |
103
+ | `repository` | string or null | Repository name when available. |
104
+ | `path` | string or null | Path within the repository when available. |
105
+ | `created` | string or null | Upstream timestamp; formatting varies by source. |
106
+ | `metadata` | object | Source-specific provenance and attributes. |
107
+ | `content_sha256` | string | SHA-256 hash used for exact content deduplication. |
108
+ | `chunk_index` | integer | Zero-based index when a long document is split. |
109
+ | `token_count` | integer | Exact `text` token count using the configured tokenizer. |
110
+
111
+ Missing provenance is represented as `null`, not inferred. Consumers should allow
112
+ source-specific keys in `metadata`.
113
+
114
+ ### Data Splits
115
+
116
+ There is one `train` split. The recipe targets the following token mixture:
117
+
118
+ | Source | Upstream dataset | Share | Nominal tokens |
119
+ | --- | --- | ---: | ---: |
120
+ | `stackv2_edu` | [`common-pile/stackv2_edu_filtered`](https://huggingface.co/datasets/common-pile/stackv2_edu_filtered) | 65.0% | 1,300,000,000 |
121
+ | `stackv2_production` | [`common-pile/stackv2`](https://huggingface.co/datasets/common-pile/stackv2) | 10.0% | 200,000,000 |
122
+ | `commitpack` | [`bigcode/commitpackft`](https://huggingface.co/datasets/bigcode/commitpackft) | 8.0% | 160,000,000 |
123
+ | `stackexchange_programming` | [`common-pile/stackexchange_filtered`](https://huggingface.co/datasets/common-pile/stackexchange_filtered) | 7.0% | 140,000,000 |
124
+ | `arxiv_cs_math` | [`common-pile/arxiv_papers_filtered`](https://huggingface.co/datasets/common-pile/arxiv_papers_filtered) | 5.0% | 100,000,000 |
125
+ | `repository_docs` | [`common-pile/stackv2_edu_filtered`](https://huggingface.co/datasets/common-pile/stackv2_edu_filtered) | 2.9% | 58,000,000 |
126
+ | `python_peps` | [`common-pile/python_enhancement_proposals_filtered`](https://huggingface.co/datasets/common-pile/python_enhancement_proposals_filtered) | 0.1% | 2,000,000 |
127
+ | `wikimedia` | [`common-pile/wikimedia_filtered`](https://huggingface.co/datasets/common-pile/wikimedia_filtered) | 2.0% | 40,000,000 |
128
+
129
+ If an upstream source is exhausted before filling its nominal allocation, the shortfall is
130
+ assigned to `stackv2_edu`. The manifest records the realized source proportions;
131
+ [`recipe.json`](recipe.json) records the target mixture and selection rules.
132
+
133
+ ### Loading the Dataset
134
+
135
+ After upload to the Hub:
136
+
137
+ ```python
138
+ from datasets import load_dataset
139
+
140
+ dataset = load_dataset("owenqwenllmwine/code-v1", split="train")
141
+ ```
142
+
143
+ To load this directory locally:
144
+
145
+ ```python
146
+ dataset = load_dataset(
147
+ "json",
148
+ data_files="data/*/train-*.jsonl.gz",
149
+ split="train",
150
+ )
151
+ ```
152
+
153
+ The card's default configuration maps all compressed JSONL shards to the `train` split.
154
+
155
+ ## Dataset Creation
156
+
157
+ ### Curation Rationale
158
+
159
+ The recipe emphasizes educational source code while retaining smaller amounts of
160
+ production code, code changes, programming discussions, repository documentation, papers,
161
+ standards, and general text. Source shares are allocated by tokenizer tokens rather than
162
+ document count or compressed size.
163
+
164
+ ### Source Data
165
+
166
+ The data is derived from the upstream Hugging Face datasets linked above. The recipe uses
167
+ seed `42`, a 10,000-example streaming shuffle buffer, a minimum document length of 32
168
+ tokens, and a maximum chunk length of 32,768 tokens. Token counts use
169
+ `Qwen/Qwen3.5-0.8B-Base`.
170
+
171
+ Processing includes:
172
+
173
+ - normalization into the common record schema;
174
+ - exact cross-source deduplication;
175
+ - long-document chunking;
176
+ - redaction of private-key blocks and common live-token patterns; and
177
+ - filtering of empty, repetitive, minified, generated, and common vendor-path content.
178
+
179
+ Educational code excludes documentation and notebooks. Production code additionally
180
+ excludes common text, lock, source-map, and tabular files. Programming Q&A is restricted
181
+ to selected programming-focused Stack Exchange sites. The exact filters are recorded in
182
+ the recipe.
183
+
184
+ ### Annotations
185
+
186
+ No new labels or human annotations were created. Language, license, provenance, and other
187
+ attributes are retained or normalized from upstream metadata.
188
+
189
+ ### Personal and Sensitive Information
190
+
191
+ Public source code and technical discussions can contain names, email addresses, usernames,
192
+ URLs, credentials, or other personal and sensitive information. Automated secret-pattern
193
+ redaction reduces some credential exposure but is not comprehensive. No dedicated PII
194
+ removal or privacy audit has been performed.
195
+
196
+ ## Considerations for Using the Data
197
+
198
+ ### Intended Use
199
+
200
+ Appropriate uses include language-model pretraining, continued pretraining, and research on
201
+ code and technical text. Users should retain provenance where needed for attribution and
202
+ perform additional filtering, decontamination, or safety review appropriate to their use
203
+ case.
204
+
205
+ ### Out-of-Scope Use
206
+
207
+ The corpus should not be treated as a source of verified, secure, up-to-date, or executable
208
+ code. It is not suitable by itself for model evaluation, supervised instruction tuning, or
209
+ applications that require factual correctness or license uniformity.
210
+
211
+ ### Biases, Risks, and Limitations
212
+
213
+ - Repository popularity, public availability, upstream sampling, and filtering choices
214
+ affect which languages, communities, and software practices are represented.
215
+ - Examples may contain vulnerabilities, obsolete APIs, incorrect answers, toxic language,
216
+ personal data, or other undesirable upstream artifacts.
217
+ - Exact duplicates are removed, but near-duplicates and benchmark contamination may remain.
218
+ - Language, license, timestamp, and provenance coverage varies by source.
219
+ - The buffered streaming shuffle is deterministic for the recorded configuration but is
220
+ not a global random permutation.
221
+ - Several upstream revisions are unpinned, so the metadata may not be sufficient to recreate
222
+ identical upstream streams in the future.
223
+
224
+ ## Licensing Information
225
+
226
+ This is a mixed-license dataset. Applicable terms vary by example and may include
227
+ permissive software licenses, public-domain material, open-content licenses, CC BY-SA, and
228
+ other licenses present in mixed-code sources. Per-record license and provenance information
229
+ is retained in `license`, `url`, `repository`, and `metadata`.
230
+
231
+ Users are responsible for reviewing and complying with the applicable terms, including
232
+ attribution and share-alike requirements. License labels are inherited from upstream
233
+ metadata and have not been independently verified. This dataset card is not legal advice.
234
+
235
+ ## Additional Information
236
+
237
+ ### Dataset Curators
238
+
239
+ Owen Qwen
240
+
241
+ ### Citation
242
+
243
+ ```bibtex
244
+ @misc{qwen2026codev1,
245
+ author = {Owen Qwen},
246
+ title = {Code Corpus code-v1},
247
+ year = {2026},
248
+ publisher = {Hugging Face},
249
+ url = {https://huggingface.co/datasets/owenqwenllmwine/code-v1}
250
+ }
251
+ ```
252
+
253
+ ### Upstream Dataset Citations
254
+
255
+ All seven unique upstream dataset repositories are linked in [Data Splits](#data-splits).
256
+ The six `common-pile` datasets share the Common Pile citation. The Stack V2-derived code
257
+ also uses The Stack V2 citation, while CommitPackFT uses the OctoPack citation.
258
+
259
+ ```bibtex
260
+ @article{kandpal2025common,
261
+ title = {The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text},
262
+ author = {Nikhil Kandpal and others},
263
+ journal = {arXiv preprint arXiv:2506.05209},
264
+ year = {2025},
265
+ url = {https://arxiv.org/abs/2506.05209}
266
+ }
267
+
268
+ @article{lozhkov2024starcoder2,
269
+ title = {StarCoder 2 and The Stack v2: The Next Generation},
270
+ author = {Anton Lozhkov and others},
271
+ journal = {arXiv preprint arXiv:2402.19173},
272
+ year = {2024},
273
+ url = {https://arxiv.org/abs/2402.19173}
274
+ }
275
+
276
+ @article{muennighoff2023octopack,
277
+ title = {OctoPack: Instruction Tuning Code Large Language Models},
278
+ author = {Niklas Muennighoff and Qian Liu and Armel Zebaze and Qinkai Zheng and
279
+ Binyuan Hui and Terry Yue Zhuo and Swayam Singh and Xiangru Tang and
280
+ Leandro von Werra and Shayne Longpre},
281
+ journal = {arXiv preprint arXiv:2308.07124},
282
+ year = {2023},
283
+ url = {https://arxiv.org/abs/2308.07124}
284
+ }
285
+ ```
286
+
287
+ These scholarly citations do not replace the attribution, notice, or share-alike
288
+ requirements of the licenses attached to individual records.
289
+
290
+ ### Reproducibility
291
+
292
+ [`manifest.json`](manifest.json) records the build timestamp, requested and realized token
293
+ counts, document and filter statistics, upstream revisions, tokenizer, and shard inventory.
294
+ [`recipe.json`](recipe.json) contains the complete source weights, filters, and processing
295
+ configuration for the release.
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