saillab/alpaca_krio_taco
收藏Hugging Face2024-09-20 更新2024-06-12 收录
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https://hf-mirror.com/datasets/saillab/alpaca_krio_taco
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资源简介:
---
language:
- kri
pretty_name: Krio 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.
---
语言:
- 克里奥尔语(Krio)
数据集展示名:Krio Alpaca-52K
规模类别:
- 10万<数据量<100万
---
本仓库存储了TaCo论文所使用的数据集。该数据集遵循TaCo论文中规定的格式,具体如下:
json
{
"instruction": "xx语言的指令",
"input": "xx语言的输入内容",
"output": "英文指令:英文原指令,
英文回复:英文原回复,
xx语言回复:xx语言原回复"
}
如需了解更多细节,请参阅该论文:[OpenReview](https://openreview.net/forum?id=02MLWBj8HP)
若您使用了本数据集,请按以下方式引用:
**引用格式**
bibtex
@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}
}
本数据集的原始版本[(Alpaca-52K)](https://github.com/tatsu-lab/stanford_alpaca?tab=readme-ov-file#data-release)通过谷歌翻译(Google Translate)完成译制。
**版权与使用用途**
本数据集采用CC BY-NC许可协议发布,仅可用于学术与研究场景。若您欲将本数据集用于研究以外的其他用途,请先查阅Alpaca-52K、Dolly-15K以及谷歌云翻译(Google Cloud Translation)的许可协议与相关条款。
提供机构:
saillab
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
数据集分割
- 训练集 (train):
- 示例数量: 49601
- 数据大小: 179505639.00459662 字节
- 测试集 (test):
- 示例数量: 12401
- 数据大小: 44879123.99540337 字节
数据集大小
- 下载大小: 109575276 字节
- 数据集总大小: 224384763.0 字节
数据文件配置
- 默认配置 (default):
- 训练集路径:
data/train-* - 测试集路径:
data/test-*
- 训练集路径:



