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---
license: cc-by-2.0
task_categories:
- table-question-answering
language:
- th
- en
tags:
- code
pretty_name: Thai-SQL_Question_generated_by_ThaiSum40k
size_categories:
- 10K<n<100K
---
# 🤖 [Super AI Engineer Development Program Season 4](https://superai.aiat.or.th/) - Pangpuriye House - ThaiSum40k
![logo](https://huggingface.co/datasets/AIAT/Pangpuriye-generated_by_typhoon/resolve/main/logo/logo.png)
## Original Dataset
We adopt this from [ThaiSum](https://huggingface.co/datasets/thaisum) dataset from `https://huggingface.co/datasets/thaisum` the original repository. We used this dataset during the fine-tuning of [Panguriye's LLM](https://huggingface.co/AIAT/Pangpuriye-openthaigpt-1.0.0-7b-chat). The dataset is available under the Creative Commons Attribution 2.0.
The original dataset consists of 380,868 rows of `title`, `body`, and `summary` in Thai. We modified this dataset by subsetting only 40,000 rows and used `จงสรุปเรื่องต่อไปนี้` as an `instruction`. The input we set by the given context, and the output is the summarization version of the given context.
We think that the `ThaiSum` dataset will aid our fine-tuning process of our instruction-tuned LLM.
During the fine-tuning phase, we want to include summaries to reduce the output length as much as feasible.
## Call Dataset
The following code is an example calling from `datasets` library.
```python
from datasets import load_dataset
dataset = load_dataset("AIAT/Pangpuriye-public_ThaiSum40k")
```
## Citation Information
We acknowledge the original dataset, and please redirect to the original paper as follow:
Please refer to the original dataset here [https://huggingface.co/datasets/thaisum](https://huggingface.co/datasets/thaisum).
```
@mastersthesis{chumpolsathien_2020,
title={Using Knowledge Distillation from Keyword Extraction to Improve the Informativeness of Neural Cross-lingual Summarization},
author={Chumpolsathien, Nakhun},
year={2020},
school={Beijing Institute of Technology}
``` |