Create README.md

README.md

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+---
+language:
+- eu
+configs:
+- config_name: booktegi
+  data_files:
+  - split: train
+    path: booktegi/train.jsonl.gz
+  - split: validation
+    path: booktegi/valid.jsonl.gz
+  - split: test
+    path: booktegi/test.jsonl.gz
+- config_name: colossal-oscar
+  data_files:
+  - split: train
+    path: colossal-oscar/train.jsonl.gz
+  - split: validation
+    path: colossal-oscar/valid.jsonl.gz
+  - split: test
+    path: colossal-oscar/test.jsonl.gz
+- config_name: culturax
+  data_files:
+  - split: train
+    path: CulturaX/train.jsonl.gz
+  - split: validation
+    path: CulturaX/valid.jsonl.gz
+  - split: test
+    path: CulturaX/test.jsonl.gz
+- config_name: egunkaria
+  data_files:
+  - split: train
+    path: egunkaria/train.jsonl.gz
+  - split: validation
+    path: egunkaria/valid.jsonl.gz
+  - split: test
+    path: egunkaria/test.jsonl.gz
+- config_name: euscrawl-v1.1
+  data_files:
+  - split: train
+    path: euscrawl-v1.1/train.jsonl.gz
+  - split: validation
+    path: euscrawl-v1.1/valid.jsonl.gz
+  - split: test
+    path: euscrawl-v1.1/test.jsonl.gz
+- config_name: hplt-v1
+  data_files:
+  - split: train
+    path: hplt-v1/train.jsonl.gz
+  - split: validation
+    path: hplt-v1/valid.jsonl.gz
+  - split: test
+    path: hplt-v1/test.jsonl.gz
+- config_name: wikipedia
+  data_files:
+  - split: test
+    path: wikipedia__20231101.test.jsonl
+task_categories:
+- fill-mask
+- text-generation
+---
+# Latxa Corpus v1.1
+
+This is the training corpus of the Latxa v1.1 base language model, a LLama 2 model trained on Basque text.
+
+- **Repository:** [https://github.com/hitz-zentroa/latxa](https://github.com/hitz-zentroa/latxa)
+- **Papers:** [Latxa: An Open Language Model and Evaluation Suite for Basque](https://arxiv.org/)
+- **Curated by:** HiTZ Research Center & IXA Research group (University of the Basque Country UPV/EHU)
+- **Language(s):** eu
+
+## Summary
+
+Latxa's training corpus combines various existing datasets, as well as some new ones that we hereby release.
+The raw document mix has been deduplicated and processed; here you'll find the final version of the corpus.
+Our data sources are introduced briefly below. 
+For more details, consult our [paper]().
+
+* **Euscrawl v1.1 <sup color="red">[new]</sup>**: An updated version of [EusCrawl v1](https://www.ixa.eus/euscrawl/) [1], including new content up to November 2023.
+* **Egunkaria <sup color="red">[new]</sup>**: Content from the Egunkaria daily newspaper.
+* **Booktegi <sup color="red">[new]</sup>**: Content from [https://www.booktegi.eus/](https://www.booktegi.eus/) EPUB books.
+* **Wikipedia**: Basque Wikipedia's [dump](https://dumps.wikimedia.org/) from November 2023.
+* **CulturaX**: The Basque portion of the [CulturaX](https://huggingface.co/datasets/uonlp/CulturaX) corpus [2].
+* **Colossal OSCAR**: The Basque portion of several [Colossal OSCAR](https://huggingface.co/datasets/oscar-corpus/colossal-oscar-1.0) releases.
+* **HPLT v1**: The Basque portion of the [HPLT v1](https://hplt-project.org/datasets/v1) [3] corpus.
+
+## Statistics
+
+The size of each dataset in terms of number of documents can be found below:
+
+|                |     Train |  Valid |   Test |
+|----------------|----------:|-------:|-------:|
+| CulturaX       | 1,283,429 | 13,096 | 13,098 |
+| EusCrawl v1.1  | 1,758,084 | 17,861 | 17,736 |
+| HPLT v1        |   367,238 |  3,797 |  3,699 |
+| Colossal OSCAR |   233,753 |  2,483 |  2,276 |
+| Wikipedia      |   400,902 |  4,063 |  4,092 |
+| Egunkaria      |   172,876 |  1,766 |  1,764 |
+| Booktegi       |       161 |      4 |      1 |
+
+
+## Citation
+
+To cite our work, please use:
+
+```bibtex
+@misc{etxaniz2024latxa,
+      title={{L}atxa: An Open Language Model and Evaluation Suite for {B}asque}, 
+      author={Julen Etxaniz and Oscar Sainz and Naiara Perez and Itziar Aldabe and German Rigau and Eneko Agirre and Aitor Ormazabal and Mikel Artetxe and Aitor Soroa},
+      year={2024},
+      eprint={},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+
+## References
+
+[1] Mikel Artetxe, Itziar Aldabe, Rodrigo Agerri, Olatz Perez-de Viñaspre, and Aitor Soroa. 2022.
+[Does corpus quality really matter for low-resource languages?](https://doi.org/10.18653/v1/2022.emnlp-main.499). 
+In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 7383–7390, Abu Dhabi, United Arab Emirates. 
+Association for Computational Linguistics.
+
+[2] Thuat Nguyen, Chien Van Nguyen, Viet Dac Lai, Hieu Man, Nghia Trung Ngo, Franck Dernoncourt, Ryan A. Rossi, and Thien Huu Nguyen. 2023. 
+[CulturaX: A cleaned, enormous, and multilingual dataset for large language models in 167 languages](https://arxiv.org/abs/2309.09400). 
+arXiv preprint arXiv:2309.09400
+
+[3] Mikko Aulamo, Nikolay Bogoychev, Shaoxiong Ji, Graeme Nail, Gema Ramírez-Sánchez, Jörg Tiedemann, Jelmer van der Linde, and Jaume Zaragoza. 2023. 
+[HPLT: High performance language technologies](https://aclanthology.org/2023.eamt-1.61). 
+In Proceedings of the 24th Annual Conference of the European Association for Machine Transla tion, pages 517–518, Tampere, Finland. 
+European Association for Machine Translation.