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README.md
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---
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dtype: string
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- name: output
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dtype: string
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splits:
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- name: train
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num_bytes: 30589076.422003
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num_examples: 41601
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- name: test
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num_bytes: 7647820.577997
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num_examples: 10401
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download_size: 25041340
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dataset_size: 38236897.0
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---
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# Dataset Card for "alpaca-latin-cleaned"
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---
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language:
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- la
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pretty_name: Latin alpaca-52k
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size_categories:
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- 100K<n<1M
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---
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This repository contains the dataset used for the TaCo paper.
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Please refer to the paper for more details: [OpenReview](https://openreview.net/forum?id=02MLWBj8HP)
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If you have used our dataset, please cite it as follows:
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**Citation**
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```
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@inproceedings{upadhayay2024taco,
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title={TaCo: Enhancing Cross-Lingual Transfer for Low-Resource Languages in {LLM}s through Translation-Assisted Chain-of-Thought Processes},
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author={Bibek Upadhayay and Vahid Behzadan},
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booktitle={5th Workshop on practical ML for limited/low resource settings, ICLR},
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year={2024},
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url={https://openreview.net/forum?id=02MLWBj8HP}
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}
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```
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The original dataset [(Alpaca-52K)](https://github.com/tatsu-lab/stanford_alpaca?tab=readme-ov-file#data-release) was translated using Google Translate.
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**Copyright and Intended Use**
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This dataset has been released under CC BY-NC, intended for academic and research purposes only. Please review the licenses and terms and conditions of Alpaca-52K, Dolly-15K, and Google Cloud Translation before using this dataset for any purpose other than research.
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