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multilingual-procedure-xlm-roberta-large-multilabel-ner
DT4H/multilingual-procedure-xlm-roberta-large-multilabel-ner
multilingual-procedure-xlm-roberta-large-multilabel-ner is a machine learning model from DT4H. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Multilingual clinical NER model for procedure recognition
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At a glance
- Model type
- xlm-roberta
- Access
- Public
- Created
- Jul 16, 2026
- Updated
- Jul 16, 2026
- SHA
- c43b466a
Model card
From the Hugging Face model README
Model Card for Multilingual-Procedure-Xlm-Roberta-Large-Multilabel
Description
Multilingual clinical NER model for procedure recognition
Model Details
- Language: MULTILINGUAL
- Task: token-classification
- Framework: pytorch
How to Use
from transformers import AutoTokenizer, AutoModelForTokenClassification
model_name = "DT4H/multilingual-procedure-xlm-roberta-large-multilabel-ner"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForTokenClassification.from_pretrained(model_name)
Citation
@inproceedings{danu2026siemens,
title={SIEMENS at\# SMM4H--HeaRD 2026: The Impact of Training Strategy and Backbone Selection on BERT-based Multilingual Clinical NER},
author={Danu, Manuela Daniela},
booktitle={Proceedings of the 11th Social Media Mining for Health Research and Applications (SMM4H-HeaRD 2026) Workshop and Shared Tasks},
pages={216--221},
year={2026}
}
Acknowledgments
This work received funding from the European Union’s Horizon Europe research and innovation programme under Grant Agreement No. 101057849 (DataTools4Heart project).
- Type
- xlm-roberta
- Languages
- multilingual
- Created
- Jul 16, 2026
- Updated
- Jul 16, 2026