holylovenia
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README.md
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- self-supervised-pretraining
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language:
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- ind
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---
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- self-supervised-pretraining
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language:
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- ind
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---
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KoPI-CC (Korpus Perayapan Indonesia)-CC is Indonesian Only Extract from Common Crawl snapshots ,each snapshots get extracted using ungoliant and get extra "filtering" using deduplication technique
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## Dataset Usage
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Run `pip install nusacrowd` before loading the dataset through HuggingFace's `load_dataset`.
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## Citation
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``` @ARTICLE{2022arXiv220106642A,
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author = {{Abadji}, Julien and {Ortiz Suarez}, Pedro and {Romary}, Laurent and {Sagot}, Benoit},
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title = "{Towards a Cleaner Document-Oriented Multilingual Crawled Corpus}",
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journal = {arXiv e-prints},
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keywords = {Computer Science - Computation and Language},
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year = 2022,
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month = jan,
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eid = {arXiv:2201.06642},
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pages = {arXiv:2201.06642},
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archivePrefix = {arXiv},
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eprint = {2201.06642},
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primaryClass = {cs.CL},
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adsurl = {https://ui.adsabs.harvard.edu/abs/2022arXiv220106642A},
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adsnote = {Provided by the SAO/NASA Astrophysics Data System}
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}
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@inproceedings{AbadjiOrtizSuarezRomaryetal.2021,
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author = {Julien Abadji and Pedro Javier Ortiz Su{'a}rez and Laurent Romary and Benoit Sagot},
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title = {Ungoliant: An optimized pipeline for the generation of a very large-scale multilingual web corpus},
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series = {Proceedings of the Workshop on Challenges in the Management of Large Corpora (CMLC-9) 2021. Limerick, 12 July 2021 (Online-Event)},
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editor = {Harald L{"u}ngen and Marc Kupietz and Piotr Bański and Adrien Barbaresi and Simon Clematide and Ines Pisetta},
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publisher = {Leibniz-Institut f{"u}r Deutsche Sprache},
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address = {Mannheim},
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doi = {10.14618/ids-pub-10468},
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url = {https://nbn-resolving.org/urn:nbn:de:bsz:mh39-104688},
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pages = {1 -- 9},
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year = {2021},
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abstract = {Since the introduction of large language models in Natural Language Processing, large raw corpora have played a crucial role in Computational Linguistics.},
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language = {en}
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}
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```
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## License
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CC0
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## Homepage
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### NusaCatalogue
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For easy indexing and metadata: [https://indonlp.github.io/nusa-catalogue](https://indonlp.github.io/nusa-catalogue)
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