Datasetpublic

BeitTigreAI/google-smol-tigre

Google SMOL - Tigre Parallel Corpus Pointer This repository provides a targeted pointer to the three English-Tigre (en_tig.jsonl) subsets from Google's google/smol dataset across its gatitos, smoldoc, and smolsent tasks. Dataset Structure The dataset contains three separate splits mapping directly to the remote source files: gatitos: Word/phrase-level translation pairs (gatitos/en_tig.jsonl) smoldoc: Document-level parallel text (smoldoc/en_tig.jsonl) smolsent:… See the full description on the dataset page: https://huggingface.co/datasets/BeitTigreAI/google-smol-tigre.

sourceHugging Faceapache-2.0updated 3d agoView on Hugging Face

1likes134downloads

Dataset Card

Google SMOL - Tigre Parallel Corpus Pointer

This repository provides a targeted pointer to the three English-Tigre (en_tig.jsonl) subsets from Google's `google/smol` dataset across its gatitos, smoldoc, and smolsent tasks.

Dataset Structure

The dataset contains three separate splits mapping directly to the remote source files:

—`gatitos`: Word/phrase-level translation pairs (gatitos/en_tig.jsonl)
—`smoldoc`: Document-level parallel text (smoldoc/en_tig.jsonl)
—`smolsent`: Sentence-level parallel text (smolsent/en_tig.jsonl)

Usage

python

from datasets import load_dataset

# Load all 3 splits into a DatasetDict
dataset = load_dataset("BeitTigreAI/google-smol-tigre")

# Load a specific split directly
smol_sentences = load_dataset("BeitTigreAI/google-smol-tigre", split="smolsent")
print(smol_sentences[0])

Citation

If you use this dataset pointer or reference the associated analysis, please cite:

bibtex

@article{tigre_smol_eval_2026,
  title={Evaluation and Architectural Analysis of Tigre Parallel Corpora in Google SMOL},
  author={Ibrahim, Beshir},
  journal={arXiv preprint arXiv:xxxx.xxxx},
  year={2026}
}