Token Classification
Transformers
Safetensors
PyTorch
English
eurobert
ner
pii
pii-detection
de-identification
privacy
healthcare
medical
clinical
phi
hipaa
openmed
custom_code
Eval Results (legacy)
Instructions to use OpenMed/OpenMed-PII-EuroMed-Large-210M-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-PII-EuroMed-Large-210M-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-PII-EuroMed-Large-210M-v1", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-PII-EuroMed-Large-210M-v1", trust_remote_code=True) model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-PII-EuroMed-Large-210M-v1", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7afa051fbe221ee65571b1957c8d626d491eccfc7f8ec1c5c2a421e4835d691
- Size of remote file:
- 17.2 MB
- SHA256:
- af5ce1447e9242961ce68b983fdda3b1948527349ee6cb8809f6b3b5d63cf686
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