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.
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.
Data Statistics
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:
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.
