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
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": null, | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|im_end|>", | |
| "errors": "replace", | |
| "is_local": false, | |
| "model_max_length": 131072, | |
| "pad_token": "<|endoftext|>", | |
| "split_special_tokens": false, | |
| "tokenizer_class": "Qwen2Tokenizer", | |
| "unk_token": null | |
| } | |