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---
language:
- ar
- de
- en
- es
- hi
- ja
- ru
- tr
- vi
- zh
task_categories:
- text-generation
configs:
- config_name: qwen3_0.6b_base_ar_10B
data_files:
- split: train
path: subsets/qwen3_0.6b_base_ar_10B/train/shard_*/data-*.arrow
- split: validation
path: subsets/qwen3_0.6b_base_ar_10B/validation/shard_*/data-*.arrow
- config_name: qwen3_0.6b_base_de_10B
data_files:
- split: train
path: subsets/qwen3_0.6b_base_de_10B/train/shard_*/data-*.arrow
- split: validation
path: subsets/qwen3_0.6b_base_de_10B/validation/shard_*/data-*.arrow
- config_name: qwen3_0.6b_base_en_30B
data_files:
- split: train
path: subsets/qwen3_0.6b_base_en_30B/train/shard_*/data-*.arrow
- split: validation
path: subsets/qwen3_0.6b_base_en_30B/validation/shard_*/data-*.arrow
- config_name: qwen3_0.6b_base_es_10B
data_files:
- split: train
path: subsets/qwen3_0.6b_base_es_10B/train/shard_*/data-*.arrow
- split: validation
path: subsets/qwen3_0.6b_base_es_10B/validation/shard_*/data-*.arrow
- config_name: qwen3_0.6b_base_hi_10B
data_files:
- split: train
path: subsets/qwen3_0.6b_base_hi_10B/train/shard_*/data-*.arrow
- split: validation
path: subsets/qwen3_0.6b_base_hi_10B/validation/shard_*/data-*.arrow
- config_name: qwen3_0.6b_base_ja_10B
data_files:
- split: train
path: subsets/qwen3_0.6b_base_ja_10B/train/shard_*/data-*.arrow
- split: validation
path: subsets/qwen3_0.6b_base_ja_10B/validation/shard_*/data-*.arrow
- config_name: qwen3_0.6b_base_ru_10B
data_files:
- split: train
path: subsets/qwen3_0.6b_base_ru_10B/train/shard_*/data-*.arrow
- split: validation
path: subsets/qwen3_0.6b_base_ru_10B/validation/shard_*/data-*.arrow
- config_name: qwen3_0.6b_base_tr_10B
data_files:
- split: train
path: subsets/qwen3_0.6b_base_tr_10B/train/shard_*/data-*.arrow
- split: validation
path: subsets/qwen3_0.6b_base_tr_10B/validation/shard_*/data-*.arrow
- config_name: qwen3_0.6b_base_vi_10B
data_files:
- split: train
path: subsets/qwen3_0.6b_base_vi_10B/train/shard_*/data-*.arrow
- split: validation
path: subsets/qwen3_0.6b_base_vi_10B/validation/shard_*/data-*.arrow
- config_name: qwen3_0.6b_base_zh_10B
data_files:
- split: train
path: subsets/qwen3_0.6b_base_zh_10B/train/shard_*/data-*.arrow
- split: validation
path: subsets/qwen3_0.6b_base_zh_10B/validation/shard_*/data-*.arrow
---
# CulturaX sampled text pools
Use `UPLOAD_COMPLETE.json` before consuming this release. Its absence means the
upload is incomplete. Pin the completed repository revision for experiments.
Original, unpacked document text from [uonlp/CulturaX](https://huggingface.co/datasets/uonlp/CulturaX).
This is a fresh sample, independent of nguyenhuuthuat09/CulturaX_sampled.
No token sequences or training caches are distributed. Each subset has a fixed
validation set and a nested training prefix suitable for smaller token budgets.
Token counts use **Qwen/Qwen3-0.6B-Base**, revision
`da87bfb608c14b7cf20ba1ce41287e8de496c0cd`. Sampling seed: **42**.
Source revision: `6a8734bc69fefcbb7735f4f9250f43e4cd7a442e`.
Each count includes one explicit `<|endoftext|>` (151643) after the document;
that marker is not appended to the stored text. Training must append it.
Tokenization has no truncation or added special tokens. Budgets round up to
whole documents and do not include packing-loss headroom. Other tokenizers can
use the text, but these counts and token-budget anchors will not apply to them.
| Subset | Training tokens including EOD | Validation tokens including EOD |
|---|---:|---:|
| qwen3_0.6b_base_ar_10B | 10,000,002,178 | 10,000,061 |
| qwen3_0.6b_base_de_10B | 10,000,001,061 | 10,000,620 |
| qwen3_0.6b_base_en_30B | 30,000,000,081 | 10,000,244 |
| qwen3_0.6b_base_es_10B | 10,000,001,093 | 10,001,384 |
| qwen3_0.6b_base_hi_10B | 10,000,001,763 | 10,008,895 |
| qwen3_0.6b_base_ja_10B | 10,000,002,841 | 10,000,048 |
| qwen3_0.6b_base_ru_10B | 10,000,001,931 | 10,009,101 |
| qwen3_0.6b_base_tr_10B | 10,000,004,885 | 10,001,348 |
| qwen3_0.6b_base_vi_10B | 10,000,000,013 | 10,000,396 |
| qwen3_0.6b_base_zh_10B | 10,000,000,321 | 10,000,728 |
```python
from datasets import load_dataset
data = load_dataset("nht10/cx_sampled", "qwen3_0.6b_base_ar_10B", revision="<completed-commit>")
```
Each `subsets/<name>/train/shard_*` and `validation/shard_*` is also a complete
`save_to_disk` folder: use `load_from_disk` and concatenate shards in sorted
order. This preserves compatibility with the existing local training loader.
Download all Arrow files referenced by each shard's `state.json`, plus
`state.json` and `dataset_info.json`. `document_index.parquet` is a row-aligned
sidecar, explicitly excluded from HF text split definitions.
`subsets/<name>/manifest.json` records ordered shard paths, counts, cumulative
endpoints, checksums, source-file identities, and every 100M-token anchor.
For an arbitrary smaller budget, select the prefix of training shards and use
the boundary shard's cumulative token index to round up to a whole document.
Keep its fixed validation split. The root manifest lists every published file.
Individual files can be downloaded using pinned HF resolve URLs; a whole-repo
download retrieves all ten subsets. Downloading files does not load a Dataset.
Sampling shuffles source files, row groups, and rows within groups with seeded
RNGs; this is not a globally uniform document shuffle. Validation is selected
first; its exact text hashes are excluded from training within each language.
There is no additional global or near-duplicate deduplication. See provenance
for the frozen sampling implementation, complete file choices and tokenizer.
## Source and license
This sample inherits the source terms. CulturaX states that its licensing
follows mC4 and OSCAR; see the preserved upstream README under provenance and
the [CulturaX dataset card](https://huggingface.co/datasets/uonlp/CulturaX).
No new license or ownership of the underlying web documents is claimed here.