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
File size: 349 Bytes
ab2f23f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"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
}
|