Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
parquet
Languages:
Thai
Size:
10M - 100M
ArXiv:
License:
metadata
language:
- th
license: other
task_categories:
- text-generation
arxiv: 2512.18834
configs:
- config_name: minhash_deduped
data_files:
- split: train
path: minhash_deduped/*.parquet
- config_name: matched
data_files:
- split: train
path: consensus/*.parquet
default: minhash_deduped
ThaiMix (https://arxiv.org/abs/2512.18834) is a Thai pretraining corpus containing 70 billion tokens across 81 million documents (in the minhash subset). Rather than scraping the web again, ThaiMix combines five publicly available Thai datasets, applies Thai-specific quality filtering, and performs cross-dataset deduplication.
Subsets
| Subset | Documents | Tokens | Description |
|---|---|---|---|
minhash_deduped |
81.3M | 70.5B | Document-level MinHash deduplication |
matched |
10.9M | 12.3B | Documents appearing in 2+ source datasets |
The matched subset uses cross-dataset agreement as a signal for quality.
Usage
from datasets import load_dataset
ds = load_dataset("AdaMLLab/ThaiMix", "minhash_deduped")
ds = load_dataset("AdaMLLab/ThaiMix", "matched")
Sources
Tokens were counted using meta-llama/Llama-3.2-3B's tokenizer.
| Source | Survival Rate |
|---|---|
| HPLT 2.0 | 75.1% |
| C4 | 72.6% |
| SEA-CC | 70.7% |
| CulturaX | 69.0% |
| FineWeb-2 | 61.7% |
Pipeline
- Quality filtering with Thai-specific thresholds (Thai script ratio, repetition patterns, language identification)
- Document-level MinHash deduplication (5-gram shingles, 14 bands, 8 hashes per band, similarity threshold 0.8)
- Cross-source matching to identify documents appearing in 2+ independent sources
Citation
@misc{alrashed2025mixminmatch,
title={Mix, MinHash, and Match: Cross-Source Agreement for Multilingual Pretraining Datasets},
author={Sultan Alrashed and Francesco Orabona},
year={2025},
eprint={2512.18834v2},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2512.18834v2},
}
License
See individual source dataset licenses.