Token Classification
Transformers
Safetensors
PyTorch
French
deberta-v2
ner
pii
pii-detection
de-identification
privacy
healthcare
medical
clinical
phi
french
openmed
Eval Results (legacy)
Instructions to use OpenMed/OpenMed-PII-French-SuperClinical-Base-184M-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-PII-French-SuperClinical-Base-184M-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-PII-French-SuperClinical-Base-184M-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-PII-French-SuperClinical-Base-184M-v1") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-PII-French-SuperClinical-Base-184M-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from OpenMed/OpenMed-PII-French-SuperClinical-Base-184M-v1: direct link, hf CLI and curl.
- Browser
- Download file 23 Bytes
-
https://huggingface.co/OpenMed/OpenMed-PII-French-SuperClinical-Base-184M-v1/resolve/main/added_tokens.json
- Command line
-
hf download hf://OpenMed/OpenMed-PII-French-SuperClinical-Base-184M-v1/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/OpenMed/OpenMed-PII-French-SuperClinical-Base-184M-v1/resolve/main/added_tokens.json
23 Bytes
| { | |
| "[MASK]": 128000 | |
| } | |