Token Classification
Transformers
Safetensors
PyTorch
Dutch
qwen3
ner
pii
pii-detection
de-identification
privacy
healthcare
medical
clinical
phi
dutch
openmed
Eval Results (legacy)
text-generation-inference
Instructions to use OpenMed/OpenMed-PII-Dutch-QwenMed-XLarge-600M-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-PII-Dutch-QwenMed-XLarge-600M-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-PII-Dutch-QwenMed-XLarge-600M-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-PII-Dutch-QwenMed-XLarge-600M-v1") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-PII-Dutch-QwenMed-XLarge-600M-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7787a188ee3ab21c51925bddec04d55393ab311f90aec48e0846ebd5d8b13230
- Size of remote file:
- 1.19 GB
- SHA256:
- e422a4b5c0fc75f89b4451c2edd7da37a0213a4fb4fe9902c81fb563104d059b
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