Datasets:
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README.md
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pretty_name: Thai-SQL_Question_generated_by_ThaiSum40k
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size_categories:
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- 10K<n<100K
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pretty_name: Thai-SQL_Question_generated_by_ThaiSum40k
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size_categories:
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- 10K<n<100K
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---
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# 🤖 [Super AI Engineer Development Program Season 4](https://superai.aiat.or.th/) - Pangpuriye House - Alpaca-Cleaned
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![logo](https://huggingface.co/datasets/AIAT/Pangpuriye-generated_by_typhoon/resolve/main/logo/logo.png)
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## Original Dataset
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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.
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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.
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We think that the `ThaiSum` dataset will aid our fine-tuning process of our instruction-tuned LLM.
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During the fine-tuning phase, we want to include summaries to reduce the output length as much as feasible.
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## Call Dataset
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The following code is an example calling from `datasets` library.
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```python
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from datasets import load_dataset
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dataset = load_dataset("AIAT/Pangpuriye-public_ThaiSum40k")
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```
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## Citation Information
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We acknowledge the original dataset, and please redirect to the original paper as follow:
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Please refer to the original dataset here [https://huggingface.co/datasets/thaisum](https://huggingface.co/datasets/thaisum).
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```
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@mastersthesis{chumpolsathien_2020,
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title={Using Knowledge Distillation from Keyword Extraction to Improve the Informativeness of Neural Cross-lingual Summarization},
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author={Chumpolsathien, Nakhun},
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year={2020},
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school={Beijing Institute of Technology}
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```
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