saillab/alpaca_sindhi_taco

---
language:
- sd
pretty_name: Sindhi 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.

This dataset includes multiple features such as instruction, input, output, id, and text, all of which are string type. The dataset is divided into a training set and a test set, containing 49601 and 12401 samples respectively. The download size of the dataset is 128586875 bytes, with a total size of 267574336.0 bytes. The dataset configuration is named default, with the training and test set data files stored in the data/train-* and data/test-* paths respectively.

原始信息汇总

数据集概述

数据集特征

• instruction：数据类型为字符串。
• input：数据类型为字符串。
• output：数据类型为字符串。
• id：数据类型为字符串。
• text：数据类型为字符串。

数据集划分

• 训练集：包含49601个样本，总大小为214056879.4544692字节。
• 测试集：包含12401个样本，总大小为53517456.54553079字节。

数据集大小

• 下载大小：128586875字节。
• 数据集总大小：267574336.0字节。

数据文件配置

• 默认配置：
  • 训练数据路径：data/train-*
  • 测试数据路径：data/test-*