README.md

---
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: instruction
    dtype: string
  - name: input
    dtype: string
  - name: output
    dtype: string
  splits:
  - name: train
    num_bytes: 2807464
    num_examples: 5760
  download_size: 1300914
  dataset_size: 2807464
license: gpl-3.0
task_categories:
- sentence-similarity
- question-answering
language:
- nl
tags:
- medical
pretty_name: Dutch translation of WikiDoc
size_categories:
- 1K<n<10K
---
# Dataset Card for "WikiDocPatientInformation_Dutch_translated_with_MariaNMT"

Translation of the **English** version of the Hugging dataset [WikiDoc patient information](https://huggingface.co/datasets/medalpaca/medical_meadow_wikidoc_patient_information), based
on [WikiDoc](https://www.wikidoc.org/index.php/Main_Page), a medical wikipedia.
to **Dutch** using an [Maria NMT model](https://marian-nmt.github.io/), trained by [Helsinki NLP](https://huggingface.co/Helsinki-NLP/opus-mt-en-nl).
Note, for reference: Maria NMT is based on [BART](https://huggingface.co/docs/transformers/model_doc/bart), described [here](https://arxiv.org/abs/1910.13461).


# Attribution

If you use this dataset please use the following to credit the creators of the OPUS-MT models:
```
@InProceedings{TiedemannThottingal:EAMT2020,
  author = {J{\"o}rg Tiedemann and Santhosh Thottingal},
  title = {{OPUS-MT} — {B}uilding open translation services for the {W}orld},
  booktitle = {Proceedings of the 22nd Annual Conferenec of the European Association for Machine Translation (EAMT)},
  year = {2020},
  address = {Lisbon, Portugal}
 }
```

and 

```
@misc {van_es_2024,
	author       = { {Bram van Es} },
	title        = { WikiDocPatientInformation_Dutch_translated_with_MariaNMT (Revision 4490701) },
	year         = 2024,
	url          = { https://huggingface.co/datasets/UMCU/WikiDocPatientInformation_Dutch_translated_with_MariaNMT },
	doi          = { 10.57967/hf/1669 },
	publisher    = { Hugging Face }
}
```

# License

For both the Maria NMT model and the original [Helsinki NLP](https://twitter.com/HelsinkiNLP) [Opus MT model](https://huggingface.co/Helsinki-NLP) 
we did **not** find a license. We also did not find a license for the MedQA corpus. For these reasons we use a permissive [CC BY](https://wellcome.org/grant-funding/guidance/open-access-guidance/creative-commons-attribution-licence-cc) 
license. If this was in error please let us know and we will add the appropriate licensing promptly.