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vngrs/vngrs-web-corpus

Dataset Card for Dataset Name vngrs-web-corpus is a mixed-dataset made of cleaned Turkish sections of OSCAR-2201 and mC4. This dataset is originally created for training VBART and later used for training TURNA. The cleaning procedures of this dataset are explained in Appendix A of the VBART Paper. It consists of 50.3M pages and 25.33B tokens when tokenized by VBART Tokenizer. Dataset Details Uses vngrs-web-corpus is mainly intended to pretrain… See the full description on the dataset page: https://huggingface.co/datasets/vngrs/vngrs-web-corpus.

sourceHugging Facecc-by-nc-sa-4.0updated 2y agoView on Hugging Face
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Dataset Card for Dataset Name

vngrs-web-corpus is a mixed-dataset made of cleaned Turkish sections of OSCAR-2201 and mC4. This dataset is originally created for training VBART and later used for training TURNA. The cleaning procedures of this dataset are explained in Appendix A of the VBART Paper. It consists of 50.3M pages and 25.33B tokens when tokenized by VBART Tokenizer.

Dataset Details

Dataset Description

  • Curated by: VNGRS-AI
  • Language (NLP): Turkish
  • License: cc-by-nc-sa-4.0

Uses

vngrs-web-corpus is mainly intended to pretrain language models and word representations.

Dataset Structure

  • text[Str]: main text content of dataset
  • corpus[Str]: source corpus
  • original_id[Int]: original index of data at the source corpus

Bias, Risks, and Limitations

This dataset holds content crawled on the open web. It is cleaned based on a set of rules and heuristics without accounting for the semantics of the content. In cases where the content is irrelevant or inappropriate, it should be flagged and removed accordingly. The dataset is intended for research purposes only and should not be used for any other purposes without prior consent from the relevant authorities.

Citation

All attributions should be made to VBART paper.

@article{turker2024vbart,
  title={VBART: The Turkish LLM},
  author={Turker, Meliksah and Ari, Erdi and Han, Aydin},
  journal={arXiv preprint arXiv:2403.01308},
  year={2024}
}