---
language:
- ne
pretty_name: Nepali alpaca-52k
size_categories:
- 100K<n<1M
---
This repository contains the dataset used for the TaCo paper.

The dataset follows the style outlined in the TaCo paper, as follows:


```
{
"instruction": "instruction in xx",
"input": "input in xx",
"output": "Instruction in English: instruction in en , 
            Response in English: response in en ,
            Response in xx: response in xx "
}
```



Please refer to the paper for more details: [OpenReview](https://openreview.net/forum?id=02MLWBj8HP)

If you have used our dataset, please cite it as follows:

**Citation**
```
@inproceedings{upadhayay2024taco,
title={TaCo: Enhancing Cross-Lingual Transfer for Low-Resource Languages in {LLM}s through Translation-Assisted Chain-of-Thought Processes},
author={Bibek Upadhayay and Vahid Behzadan},
booktitle={5th Workshop on practical ML for limited/low resource settings, ICLR},
year={2024},
url={https://openreview.net/forum?id=02MLWBj8HP}
}
```

The original dataset [(Alpaca-52K)](https://github.com/tatsu-lab/stanford_alpaca?tab=readme-ov-file#data-release) was translated using Google Translate.

**Copyright and Intended Use**
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.