AIAT/Pangpuriye-generated_by_LLama3-codeLlama

---
license: cc-by-nc-2.0
task_categories:
- table-question-answering
language:
- th
- en
tags:
- code
- sql
pretty_name: Thai-SQL_Question_generated_by_LLama3-codeLlama
size_categories:
- 10K<n<100K
---

# 🤖 [Super AI Engineer Development Program Season 4](https://superai.aiat.or.th/) - Pangpuriye House - Generated by LLama3+codeLlama


**Pangpuriye's House Dataset - Generated Dataset from LLama3+codeLlama**

The dataset is a pack of text generation from [LLama3](https://ai.meta.com/blog/meta-llama-3/) and [codeLlama](https://ai.meta.com/blog/code-llama-large-language-model-coding/). The dataset is set under cc-by-nc-2.0 license.

## Content

The dataset consists of 54,033 rows of `input`, `instruction`, and `output`. Most of the context in the dataset is in Thai. Whereas, the `output` is generally the answers regarding instruction equestion in numeric and logical answers.

## Uses

The dataset is intended to be used as an instruction for fine-tuning table-based QA LLM. The instruction requires some processing before it can be utilized in the process.

## Call our dataset by `datasets` library

The following code is an example of calling our dataset by the `datasets` library.

```python
from datasets import load_dataset

dataset = load_dataset("Pangpuriye-generated_by_LLama3-codeLlama")
```

## Acknowledgements

The dataset is collectively stored by the members of Panguriye's house during the LLMs hackathon in Super AI Engineer Development Program Season 4.

We thank the organizers of this hackathon, [OpenThaiGPT](https://openthaigpt.aieat.or.th/), [AIAT](https://aiat.or.th/), [NECTEC](https://www.nectec.or.th/en/) and [ThaiSC](https://thaisc.io/) for this challenging task and opportunity to be a part of developing Thai large language model.

## Citation Information

We thank Llama 3 and codeLlama for a huge contribution in our hackathon's dataset generation process.

```
@article{llama3modelcard,
title={Llama 3 Model Card},
author={AI@Meta},
year={2024},
url = {https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md}
}
```

```
@misc{rozière2024code,
title={Code Llama: Open Foundation Models for Code},
author={Baptiste Rozière and Jonas Gehring and Fabian Gloeckle and Sten Sootla and Itai Gat and Xiaoqing Ellen Tan and Yossi Adi and Jingyu Liu and Romain Sauvestre and Tal Remez and Jérémy Rapin and Artyom Kozhevnikov and Ivan Evtimov and Joanna Bitton and Manish Bhatt and Cristian Canton Ferrer and Aaron Grattafiori and Wenhan Xiong and Alexandre Défossez and Jade Copet and Faisal Azhar and Hugo Touvron and Louis Martin and Nicolas Usunier and Thomas Scialom and Gabriel Synnaeve},
year={2024},
eprint={2308.12950},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```

原始信息汇总

数据集概述

基本信息

• 许可证: cc-by-nc-2.0
• 任务类别: 表格问答
• 语言: 泰语, 英语
• 标签: 代码, SQL
• 美观名称: Thai-SQL_Question_generated_by_LLama3-codeLlama
• 大小类别: 10K<n<100K

内容描述

• 数据集组成: 包含54,033行数据，包括input, instruction, 和output。
• 数据特点: 大部分内容为泰语，output通常为关于指令的数字和逻辑答案。

用途

• 主要用途: 用于微调基于表格的问答大型语言模型。
• 使用前处理: 需要进行一定的预处理才能使用。

数据集调用

• 调用示例: python from datasets import load_dataset dataset = load_dataset("Pangpuriye-generated_by_LLama3-codeLlama")