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ai-enthusiasm-community/vietnamese_health_dataset

Team and Homepage Official Website: https://aienthusiasm.vn Hugging Face Organization: https://huggingface.co/ai-enthusiasm-community Contact If you encounter any issues with the dataset or have any inquiries, please feel free to reach out to us via email at: aienthusiasm.team@gmail.com Dataset Structure The dataset is provided in a flattened tabular format, optimized for the Hugging Face Dataset Viewer and high-speed Parquet processing.… See the full description on the dataset page: https://huggingface.co/datasets/ai-enthusiasm-community/vietnamese_health_dataset.

sourceHugging Facemitupdated 4mo agoView on Hugging Face
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Dataset Card

Team and Homepage

Contact

If you encounter any issues with the dataset or have any inquiries, please feel free to reach out to us via email at: aienthusiasm.team@gmail.com

Dataset Structure

The dataset is provided in a flattened tabular format, optimized for the Hugging Face Dataset Viewer and high-speed Parquet processing.

Data Statistics

Total ContextsTotal QA Pairs
752,8674,376,621

Data Fields

  • —id: The identification string of the context, matching the ID format from the source corpus VTSNLP/vietnamese_curated_dataset.
  • —context: The raw Vietnamese text providing the background information.
  • —qa_records: List of multilingual question-answer pairs derived directly from the context, following the format [{question_vi, question_en, answer_vi, answer_en}].

Usage

The dataset can be accessed directly using the Hugging Face datasets library:

python
from datasets import load_dataset

dataset = load_dataset("ai-enthusiasm-community/vietnamese_health_dataset")

# Accessing the first sample
print(dataset['train'][0])

Disclaimer

This is a synthetically generated dataset derived from publicly available resources using artificial intelligence models. Consequently, the data may contain factual inaccuracies, machine artifacts, or omissions. This corpus is intended solely for research and development purposes; it is not validated for clinical use or direct deployment in production environments. Users are strongly advised to perform rigorous verification and manual curation prior to any downstream applications.