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pythainlp/han-instruct-dataset-v2.0

Dataset Card for Han Instruct Dataset v2.0 The newest dataset version is https://huggingface.co/datasets/pythainlp/han-instruction-dataset. 🪿 Han (ห่าน or goose) Instruct Dataset is a Thai instruction dataset by PyThaiNLP. This dataset collect all Thai instruct dataset that made by human and our old model. The dataset can use to train Instruction Following model like ChatGPT or other. Many question are collect from Reference desk at Thai wikipedia. Data sources: Reference desk… See the full description on the dataset page: https://huggingface.co/datasets/pythainlp/han-instruct-dataset-v2.0.

sourceHugging Facecc-by-sa-4.0updated 6d agoView on Hugging Face
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Dataset Card

Dataset Card for Han Instruct Dataset v2.0

The newest dataset version is [https://huggingface.co/datasets/pythainlp/han-instruction-dataset](https://huggingface.co/datasets/pythainlp/han-instruction-dataset).

🪿 Han (ห่าน or goose) Instruct Dataset is a Thai instruction dataset by PyThaiNLP. This dataset collect all Thai instruct dataset that made by human and our old model. The dataset can use to train Instruction Following model like ChatGPT or other.

Many question are collect from Reference desk at Thai wikipedia.

Data sources:

Supported Tasks and Leaderboards

  • —ChatBot
  • —Instruction Following

Languages

Thai

Dataset Structure

Data Fields

  • —q: Question
  • —a: Answer

Considerations for Using the Data

The dataset can has a biased from human annotators. We recommend you should checked the dataset to select or remove an instruct follow before train the model or use it own your risk.

Licensing Information

CC-BY-SA 4.0

Citation

If you use Han Instruct Dataset (v2.0) in your project or publication, please cite the dataset as follows:

Phatthiyaphaibun, W. (2024). Han Instruct Dataset (v2.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10935857

or

bib
@dataset{phatthiyaphaibun_2024_10935857,
  author       = {Phatthiyaphaibun, Wannaphong},
  title        = {Han Instruct Dataset},
  month        = apr,
  year         = 2024,
  publisher    = {Zenodo},
  version      = {v2.0},
  doi          = {10.5281/zenodo.10935857},
  url          = {https://doi.org/10.5281/zenodo.10935857}
}

Zenodo: https://doi.org/10.5281/zenodo.10935857