Datasets:

m8than
/

cortex-20b

---
license: odc-by
task_categories:
  - text-generation
  - fill-mask
language:
  - en
  - ja
tags:
  - pretraining
  - web
  - code
  - encyclopedic
  - dialogue
  - balanced-mixture
  - 20b-tokens
  - 100b-characters
  - cortex
size_categories:
  - 10M<n<100M
---
# cortex-20b

A 20 B-token (100 B-character), cap-balanced English/Japanese
pretraining mixture assembled for general-purpose language model
training. Release tag `v0.9` (mixture build `balanced-pretraining-v8`,
finalized 2026-09-15).

The dataset is partitioned into three splits (`train`, `validation`,
`test`) and stores 22.4 M text records on disk in zstd-compressed
Parquet. The source stream spans web text, encyclopedias, news,
public-domain books, academic articles, patents, court documents, code,
Reddit submissions, Japanese web fiction, dialogue/game transcripts,
and OpenStreetMap/Overture spatial data.

## At a glance

| Split | Records | Characters (text) | Bytes (raw JSONL) | Parquet shards |
| --- | ---: | ---: | ---: | ---: |
| `train` | 22,426,697 | 96,963,026,897 | 127,541,814,421 (127 GB) | 113 × ~400 MB |
| `validation` | 17,087 | 124,708,316 | 145,751,270 (140 MB) | 1 |
| `test` | 16,773 | 103,121,121 | 123,351,487 (118 MB) | 1 |
| **Total** | **22,460,557** | **97,190,856,334** | **127,810,917,178** | **115** |

Approximate tokens (4 chars/token heuristic): **24.3 B** — round-figure
label `cortex-20b` is what the card sticks to; the heuristic
under-counts multilingual content.

## Load

```python
from datasets import load_dataset
# Full mix (streaming-friendly, 22.4 M rows).
ds = load_dataset("m8than/cortex-20b", split="train")
# Just validation / test.
val = load_dataset("m8than/cortex-20b", split="validation")
test = load_dataset("m8than/cortex-20b", split="test")
# Or by category / source dataset:
dclm = load_dataset("m8than/cortex-20b", split="train").filter(
    lambda r: "HuggingFaceTB/dclm-edu" in r["source"]
)
# Streaming (recommended for the full train split):
ds = load_dataset("m8than/cortex-20b", split="train", streaming=True)
for row in ds:
    ...
```

Each row has the schema below:

| Column | Type | Description |
| --- | --- | --- |
| `id` | `string` | Stable per-record id (preserved from upstream datasets where possible). |
| `kind` | `string` | Always `"text"` for this release. |
| `source` | `string` (JSON) | Upstream provenance block as JSON (dataset, license, URL, IDs, etc.). |
| `quality` | `string` (JSON) | Quality/filtering metadata as JSON (version, tier, score, flags, metrics). |
| `mixture` | `string` (JSON) | Per-record mixture-bucket info as JSON (input source, cap, license gate). |
| `extra` | `string` (JSON) | Any record-level fields that don't fit the columns above (e.g. `legal_moves`, `action`, `messages`, `annotations`). Empty for most rows. |
| `text` | `string` | The training text itself. |
| `split_group` | `string` | Stable cross-split identity used for split construction (provenance key, family id, etc.). Rows lacking one are train-only. |

## Build summary

- **Mixture version:** 8 (`mixture_config: data/config/mixture-v8.json`,
  sha256 `8554981b…51de96`).
- **Release tag:** `v0.9` (mixture build is `balanced-pretraining-v8`).
- **Seed:** `balanced-v8` (sampling), `balanced-v3-split` (splitting).
- **Split ratios:** train 98 % / validation 1 % / test 1 %, split at the
  `source.split_group` level where one exists; otherwise train-only.
- **Determinism:** exact text deduplication (142,339 dupes dropped) and
  deterministic per-bucket rank-based subsampling so the release is
  reproducible bit-for-bit given the same seed.
- **Verification:** `python scripts/build_release.py --audit release-v8`
  confirms `malformed_records=0`, `cross_split_group_records=0`,
  `expected_split_mismatches=0`.

## Category breakdown (final, post-dedup)

| Category | Records | Text chars | Share |
| --- | ---: | ---: | ---: |
| general (web, encyclopedias, news, speech, social) | 15,686,992 | 41,030,478,036 | 42.3 % |
| code (Stack v3 + Nemotron-CC-Code) | 5,910,855 | 43,385,459,535 | 44.7 % |
| academic (arXiv, PubMed, USPTO, free law, MedQA) | 155,000 | 3,834,484,147 | 3.9 % |
| books (Gutenberg, US-PD, LoC-PD) | 6,629 | 2,301,415,159 | 2.4 % |
| fiction (Japanese web novels) | 215,854 | 4,999,969,532 | 5.1 % |
| dialogue (CRD3, FIREBALL, Hanabi, blackjack, …) | 196,802 | 424,223,265 | 0.4 % |
| spatial (OpenStreetMap, Overture) | 254,565 | 986,997,223 | 1.0 % |

## Source attribution

All inputs are listed below with their upstream HF identifier, license,
upstream URL, and the post-dedup record count that ended up in this
release.

| Source dataset | License | Records | Upstream |
| --- | --- | ---: | --- |
| `nvidia/Nemotron-CC-Code-v1` | CC-BY-4.0 | 5,677,001 | https://huggingface.co/datasets/nvidia/Nemotron-CC-Code-v1 |
| `Zyphra/Zyda-2` | CC-BY-4.0 / ODbL | 3,414,053 | https://huggingface.co/datasets/Zyphra/Zyda-2 |
| `HuggingFaceTB/dclm-edu` | CC-BY-4.0 | 2,408,652 | https://huggingface.co/datasets/HuggingFaceTB/dclm-edu |
| `common-pile/wikiteam_filtered` | CC-BY-SA 3.0/4.0 | 594,267 | https://huggingface.co/datasets/common-pile/wikiteam_filtered |
| `HuggingFaceFW/finewiki` | CC-BY-SA 4.0 | 396,723 | https://huggingface.co/datasets/HuggingFaceFW/finewiki |
| `HuggingFaceCode/stack-v3-train` | per-file | 233,854 | https://huggingface.co/datasets/HuggingFaceCode/stack-v3-train |
| `tvtropes` | CC-BY-NC-SA-3.0 | 233,704 | https://tvtropes.org (WikiTeam extract, see manifest for provenance) |
| `syosetu` | LicenseRef-HF-p1atdev-syosetu711k | 215,854 | https://huggingface.co/datasets/p1atdev/syosetu711k |
| `open2roam/openstreetmaps` | ODbL-1.0 | 202,488 | https://huggingface.co/datasets/open2roam/openstreetmaps |
| `lara-martin/FIREBALL` | MIT (derived) | 121,042 | https://huggingface.co/datasets/lara-martin/FIREBALL |
| `common-pile/news_filtered` | per-source | 105,818 | https://huggingface.co/datasets/common-pile/news_filtered |
| `common-pile/uspto_filtered` | CC-BY-4.0 | 62,377 | https://huggingface.co/datasets/common-pile/uspto_filtered |
| `common-pile/youtube_filtered` | CC-BY-4.0 | 62,147 | https://huggingface.co/datasets/common-pile/youtube_filtered |
| `overturemaps/places` | ODbL-1.0 | 52,077 | https://huggingface.co/datasets/overturemaps/places |
| `common-pile/pubmed_filtered` | CC0 / per-article | 44,564 | https://huggingface.co/datasets/common-pile/pubmed_filtered |
| `common-pile/caselaw_access_project_filtered` | public-domain (US) | 34,007 | https://huggingface.co/datasets/common-pile/caselaw_access_project_filtered |
| `Mahesh111000/Hanabi_dataset` | MIT | 29,965 | https://huggingface.co/datasets/Mahesh111000/Hanabi_dataset |
| `microsoft/crd3` | CC-BY-4.0 | 27,744 | https://huggingface.co/datasets/microsoft/crd3 |
| `steam/appreviews-wide` | Steam-Valve-Terms | 12,880 | https://huggingface.co/datasets/steam/appreviews |
| `GBaker/MedQA-USMLE-4-options` | MIT | 10,176 | https://huggingface.co/datasets/GBaker/MedQA-USMLE-4-options |
| `common-pile/project_gutenberg_filtered` | public-domain | 5,941 | https://huggingface.co/datasets/common-pile/project_gutenberg_filtered |
| `scholarweave/arxiv-latex` | per-paper (allowlisted: CC0/CC-BY/CC-BY-SA) | 3,876 | https://huggingface.co/datasets/scholarweave/arxiv-latex |
| `steam/appreviews` | Steam-Valve-Terms | 2,704 | https://huggingface.co/datasets/steam/appreviews |
| `blackjack-open-rules` | public-domain | 2,443 | upstream rules document |
| `storytracer/US-PD-Books` | public-domain | 527 | https://huggingface.co/datasets/storytracer/US-PD-Books |
| `storytracer/LoC-PD-Books` | public-domain | 161 | https://huggingface.co/datasets/storytracer/LoC-PD-Books |
| `Idrinth/gamemasterai` | MIT (upstream roleplay-ai) | 24 | https://huggingface.co/datasets/Idrinth/gamemasterai |
| `reddit/pushshift-submissions` | LicenseRef-Pushshift-Research (research only) | 8,471,628 | Pushshift mirror |
The Pushshift/Reddit slice is included for research use under the
[Pushshift research license](https://files.pushshift.io/redacts/).
Downstream commercial model weights derived from this dataset may need
to remove or replace the Reddit slice; consult your legal counsel.
## License
This dataset is released as a **mixture** under the [Open Data Commons
Attribution License 1.0](https://opendatacommons.org/licenses/by/) (ODC-BY
1.0). Each individual record retains its upstream license — see the
`source.license` field on every row and the rights review embedded in
`auxiliary_metadata/manifest.json`. Applying this mixture to train a
model requires that downstream use respects the most restrictive
per-input license (in particular: NC clauses from TVTropes, research-use
terms from Pushshift, per-file Stack v3 licenses).

## Rights review

The full per-source rights review (date 2026-09-05) is included in
`auxiliary_metadata/manifest.json` under `rights_review`. Highlights:

- **Excluded**: `mastermind`, `europarl` (pending provenance),
  `wikimedical` (derivative of FineWiki), `terraria-wiki`,
  `minecraft-wiki` (NC on primary sources), `dnd-dm-v3` (no verifiable
  upstream).
- **Per-paper allowlist**: arXiv only includes CC0/CC-BY/CC-BY-SA
  submissions; NC/ND/unknown were rejected before sampling (83,711
  records / 31.6 B characters dropped).
- **Pushshift/Reddit**: included under research license only.
- **Steam reviews**: included under Steam/Valve terms.

## Repository layout

```
.
├── README.md
├── LICENSE                                # ODC-BY 1.0
├── dataset_infos.json                     # features / split sizes for load_dataset
├── auxiliary_metadata/
│   ├── manifest.json                      # Full v8 build manifest
│   ├── finalize.manifest.json             # Finalize-stage manifest
│   ├── verification.json                  # Audit script output
│   └── SHA256SUMS                         # Per-file SHA256s of the original JSONL
└── data/
    ├── train-00000.parquet
    ├── train-00001.parquet
    ├── …
    ├── train-00112.parquet
    ├── validation-00000.parquet
    └── test-00000.parquet
```

Parquet files are zstd-compressed, ~400 MB each (200,000 records per
train shard). Load with `datasets.load_dataset(..., split="train")` or
stream shard-by-shard via `streaming=True`.

## Provenance and reproducibility

- Built with `python scripts/build_release.py --mixture
  data/config/mixture-v8.json`.
- Sampling seed: `balanced-v8`. Splitting seed: `balanced-v3-split`.
- Each shard's SHA256 is recorded in
  `auxiliary_metadata/shard_stats.jsonl` (generated alongside the
  upload).
- The original JSONL split files are hashed in `auxiliary_metadata/SHA256SUMS`.

## Cite

```bibtex
@misc{cortex-20b,
  title  = {cortex-20b: a 100B-character / 20B-token cap-balanced pretraining mixture (v0.9)},
  author = {Wilce, Nathan},
  year   = {2026},
  url    = {https://huggingface.co/datasets/m8than/cortex-20b},
}
```

	---
	license: odc-by
	task_categories:
	- text-generation
	- fill-mask
	language:
	- en
	- ja
	tags:
	- pretraining
	- web
	- code
	- encyclopedic
	- dialogue
	- balanced-mixture
	- 20b-tokens
	- 100b-characters
	- cortex
	size_categories:
	- 10M<n<100M
	---

	# cortex-20b

	A 20 B-token (100 B-character), cap-balanced English/Japanese
	pretraining mixture assembled for general-purpose language model
	training. Release tag `v0.9` (mixture build `balanced-pretraining-v8`,
	finalized 2026-09-15).

	The dataset is partitioned into three splits (`train`, `validation`,
	`test`) and stores 22.4 M text records on disk in zstd-compressed
	Parquet. The source stream spans web text, encyclopedias, news,
	public-domain books, academic articles, patents, court documents, code,
	Reddit submissions, Japanese web fiction, dialogue/game transcripts,
	and OpenStreetMap/Overture spatial data.

	## At a glance

	\| Split \| Records \| Characters (text) \| Bytes (raw JSONL) \| Parquet shards \|
	\| --- \| ---: \| ---: \| ---: \| ---: \|
	\| `train` \| 22,426,697 \| 96,963,026,897 \| 127,541,814,421 (127 GB) \| 113 × ~400 MB \|
	\| `validation` \| 17,087 \| 124,708,316 \| 145,751,270 (140 MB) \| 1 \|
	\| `test` \| 16,773 \| 103,121,121 \| 123,351,487 (118 MB) \| 1 \|
	\| Total \| 22,460,557 \| 97,190,856,334 \| 127,810,917,178 \| 115 \|

	Approximate tokens (4 chars/token heuristic): 24.3 B — round-figure
	label `cortex-20b` is what the card sticks to; the heuristic
	under-counts multilingual content.

	## Load

	```python
	from datasets import load_dataset

	# Full mix (streaming-friendly, 22.4 M rows).
	ds = load_dataset("m8than/cortex-20b", split="train")

	# Just validation / test.
	val = load_dataset("m8than/cortex-20b", split="validation")
	test = load_dataset("m8than/cortex-20b", split="test")

	# Or by category / source dataset:
	dclm = load_dataset("m8than/cortex-20b", split="train").filter(
	lambda r: "HuggingFaceTB/dclm-edu" in r["source"]
	)

	# Streaming (recommended for the full train split):
	ds = load_dataset("m8than/cortex-20b", split="train", streaming=True)
	for row in ds:
	...
	```

	Each row has the schema below:

	\| Column \| Type \| Description \|
	\| --- \| --- \| --- \|
	\| `id` \| `string` \| Stable per-record id (preserved from upstream datasets where possible). \|
	\| `kind` \| `string` \| Always `"text"` for this release. \|
	\| `source` \| `string` (JSON) \| Upstream provenance block as JSON (dataset, license, URL, IDs, etc.). \|
	\| `quality` \| `string` (JSON) \| Quality/filtering metadata as JSON (version, tier, score, flags, metrics). \|
	\| `mixture` \| `string` (JSON) \| Per-record mixture-bucket info as JSON (input source, cap, license gate). \|
	\| `extra` \| `string` (JSON) \| Any record-level fields that don't fit the columns above (e.g. `legal_moves`, `action`, `messages`, `annotations`). Empty for most rows. \|
	\| `text` \| `string` \| The training text itself. \|
	\| `split_group` \| `string` \| Stable cross-split identity used for split construction (provenance key, family id, etc.). Rows lacking one are train-only. \|

	## Build summary

	- Mixture version: 8 (`mixture_config: data/config/mixture-v8.json`,
	sha256 `8554981b…51de96`).
	- Release tag: `v0.9` (mixture build is `balanced-pretraining-v8`).
	- Seed: `balanced-v8` (sampling), `balanced-v3-split` (splitting).
	- Split ratios: train 98 % / validation 1 % / test 1 %, split at the
	`source.split_group` level where one exists; otherwise train-only.
	- Determinism: exact text deduplication (142,339 dupes dropped) and
	deterministic per-bucket rank-based subsampling so the release is
	reproducible bit-for-bit given the same seed.
	- Verification: `python scripts/build_release.py --audit release-v8`
	confirms `malformed_records=0`, `cross_split_group_records=0`,
	`expected_split_mismatches=0`.

	## Category breakdown (final, post-dedup)

	\| Category \| Records \| Text chars \| Share \|
	\| --- \| ---: \| ---: \| ---: \|
	\| general (web, encyclopedias, news, speech, social) \| 15,686,992 \| 41,030,478,036 \| 42.3 % \|
	\| code (Stack v3 + Nemotron-CC-Code) \| 5,910,855 \| 43,385,459,535 \| 44.7 % \|
	\| academic (arXiv, PubMed, USPTO, free law, MedQA) \| 155,000 \| 3,834,484,147 \| 3.9 % \|
	\| books (Gutenberg, US-PD, LoC-PD) \| 6,629 \| 2,301,415,159 \| 2.4 % \|
	\| fiction (Japanese web novels) \| 215,854 \| 4,999,969,532 \| 5.1 % \|
	\| dialogue (CRD3, FIREBALL, Hanabi, blackjack, …) \| 196,802 \| 424,223,265 \| 0.4 % \|
	\| spatial (OpenStreetMap, Overture) \| 254,565 \| 986,997,223 \| 1.0 % \|

	## Source attribution

	All inputs are listed below with their upstream HF identifier, license,
	upstream URL, and the post-dedup record count that ended up in this
	release.

	\| Source dataset \| License \| Records \| Upstream \|
	\| --- \| --- \| ---: \| --- \|
	\| `nvidia/Nemotron-CC-Code-v1` \| CC-BY-4.0 \| 5,677,001 \| https://huggingface.co/datasets/nvidia/Nemotron-CC-Code-v1 \|
	\| `Zyphra/Zyda-2` \| CC-BY-4.0 / ODbL \| 3,414,053 \| https://huggingface.co/datasets/Zyphra/Zyda-2 \|
	\| `HuggingFaceTB/dclm-edu` \| CC-BY-4.0 \| 2,408,652 \| https://huggingface.co/datasets/HuggingFaceTB/dclm-edu \|
	\| `common-pile/wikiteam_filtered` \| CC-BY-SA 3.0/4.0 \| 594,267 \| https://huggingface.co/datasets/common-pile/wikiteam_filtered \|
	\| `HuggingFaceFW/finewiki` \| CC-BY-SA 4.0 \| 396,723 \| https://huggingface.co/datasets/HuggingFaceFW/finewiki \|
	\| `HuggingFaceCode/stack-v3-train` \| per-file \| 233,854 \| https://huggingface.co/datasets/HuggingFaceCode/stack-v3-train \|
	\| `tvtropes` \| CC-BY-NC-SA-3.0 \| 233,704 \| https://tvtropes.org (WikiTeam extract, see manifest for provenance) \|
	\| `syosetu` \| LicenseRef-HF-p1atdev-syosetu711k \| 215,854 \| https://huggingface.co/datasets/p1atdev/syosetu711k \|
	\| `open2roam/openstreetmaps` \| ODbL-1.0 \| 202,488 \| https://huggingface.co/datasets/open2roam/openstreetmaps \|
	\| `lara-martin/FIREBALL` \| MIT (derived) \| 121,042 \| https://huggingface.co/datasets/lara-martin/FIREBALL \|
	\| `common-pile/news_filtered` \| per-source \| 105,818 \| https://huggingface.co/datasets/common-pile/news_filtered \|
	\| `common-pile/uspto_filtered` \| CC-BY-4.0 \| 62,377 \| https://huggingface.co/datasets/common-pile/uspto_filtered \|
	\| `common-pile/youtube_filtered` \| CC-BY-4.0 \| 62,147 \| https://huggingface.co/datasets/common-pile/youtube_filtered \|
	\| `overturemaps/places` \| ODbL-1.0 \| 52,077 \| https://huggingface.co/datasets/overturemaps/places \|
	\| `common-pile/pubmed_filtered` \| CC0 / per-article \| 44,564 \| https://huggingface.co/datasets/common-pile/pubmed_filtered \|
	\| `common-pile/caselaw_access_project_filtered` \| public-domain (US) \| 34,007 \| https://huggingface.co/datasets/common-pile/caselaw_access_project_filtered \|
	\| `Mahesh111000/Hanabi_dataset` \| MIT \| 29,965 \| https://huggingface.co/datasets/Mahesh111000/Hanabi_dataset \|
	\| `microsoft/crd3` \| CC-BY-4.0 \| 27,744 \| https://huggingface.co/datasets/microsoft/crd3 \|
	\| `steam/appreviews-wide` \| Steam-Valve-Terms \| 12,880 \| https://huggingface.co/datasets/steam/appreviews \|
	\| `GBaker/MedQA-USMLE-4-options` \| MIT \| 10,176 \| https://huggingface.co/datasets/GBaker/MedQA-USMLE-4-options \|
	\| `common-pile/project_gutenberg_filtered` \| public-domain \| 5,941 \| https://huggingface.co/datasets/common-pile/project_gutenberg_filtered \|
	\| `scholarweave/arxiv-latex` \| per-paper (allowlisted: CC0/CC-BY/CC-BY-SA) \| 3,876 \| https://huggingface.co/datasets/scholarweave/arxiv-latex \|
	\| `steam/appreviews` \| Steam-Valve-Terms \| 2,704 \| https://huggingface.co/datasets/steam/appreviews \|
	\| `blackjack-open-rules` \| public-domain \| 2,443 \| upstream rules document \|
	\| `storytracer/US-PD-Books` \| public-domain \| 527 \| https://huggingface.co/datasets/storytracer/US-PD-Books \|
	\| `storytracer/LoC-PD-Books` \| public-domain \| 161 \| https://huggingface.co/datasets/storytracer/LoC-PD-Books \|
	\| `Idrinth/gamemasterai` \| MIT (upstream roleplay-ai) \| 24 \| https://huggingface.co/datasets/Idrinth/gamemasterai \|
	\| `reddit/pushshift-submissions` \| LicenseRef-Pushshift-Research (research only) \| 8,471,628 \| Pushshift mirror \|

	The Pushshift/Reddit slice is included for research use under the
	[Pushshift research license](https://files.pushshift.io/redacts/).
	Downstream commercial model weights derived from this dataset may need
	to remove or replace the Reddit slice; consult your legal counsel.

	## License

	This dataset is released as a mixture under the [Open Data Commons
	Attribution License 1.0](https://opendatacommons.org/licenses/by/) (ODC-BY
	1.0). Each individual record retains its upstream license — see the
	`source.license` field on every row and the rights review embedded in
	`auxiliary_metadata/manifest.json`. Applying this mixture to train a
	model requires that downstream use respects the most restrictive
	per-input license (in particular: NC clauses from TVTropes, research-use
	terms from Pushshift, per-file Stack v3 licenses).

	## Rights review

	The full per-source rights review (date 2026-09-05) is included in
	`auxiliary_metadata/manifest.json` under `rights_review`. Highlights:

	- Excluded: `mastermind`, `europarl` (pending provenance),
	`wikimedical` (derivative of FineWiki), `terraria-wiki`,
	`minecraft-wiki` (NC on primary sources), `dnd-dm-v3` (no verifiable
	upstream).
	- Per-paper allowlist: arXiv only includes CC0/CC-BY/CC-BY-SA
	submissions; NC/ND/unknown were rejected before sampling (83,711
	records / 31.6 B characters dropped).
	- Pushshift/Reddit: included under research license only.
	- Steam reviews: included under Steam/Valve terms.

	## Repository layout

	```
	.
	├── README.md
	├── LICENSE # ODC-BY 1.0
	├── dataset_infos.json # features / split sizes for load_dataset
	├── auxiliary_metadata/
	│ ├── manifest.json # Full v8 build manifest
	│ ├── finalize.manifest.json # Finalize-stage manifest
	│ ├── verification.json # Audit script output
	│ └── SHA256SUMS # Per-file SHA256s of the original JSONL
	└── data/
	├── train-00000.parquet
	├── train-00001.parquet
	├── …
	├── train-00112.parquet
	├── validation-00000.parquet
	└── test-00000.parquet
	```

	Parquet files are zstd-compressed, ~400 MB each (200,000 records per
	train shard). Load with `datasets.load_dataset(..., split="train")` or
	stream shard-by-shard via `streaming=True`.

	## Provenance and reproducibility

	- Built with `python scripts/build_release.py --mixture
	data/config/mixture-v8.json`.
	- Sampling seed: `balanced-v8`. Splitting seed: `balanced-v3-split`.
	- Each shard's SHA256 is recorded in
	`auxiliary_metadata/shard_stats.jsonl` (generated alongside the
	upload).
	- The original JSONL split files are hashed in `auxiliary_metadata/SHA256SUMS`.

	## Cite

	```bibtex
	@misc{cortex-20b,
	title = {cortex-20b: a 100B-character / 20B-token cap-balanced pretraining mixture (v0.9)},
	author = {Wilce, Nathan},
	year = {2026},
	url = {https://huggingface.co/datasets/m8than/cortex-20b},
	}
	```