Token Classification
Transformers
Safetensors
PyTorch
German
bert
ner
pii
pii-detection
de-identification
privacy
healthcare
medical
clinical
phi
german
openmed
Eval Results (legacy)
Instructions to use OpenMed/OpenMed-PII-German-BiomedBERT-Base-110M-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-PII-German-BiomedBERT-Base-110M-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-PII-German-BiomedBERT-Base-110M-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-PII-German-BiomedBERT-Base-110M-v1") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-PII-German-BiomedBERT-Base-110M-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from OpenMed/OpenMed-PII-German-BiomedBERT-Base-110M-v1: direct link, hf CLI and curl.
- Browser
- Download file 125 Bytes
-
https://huggingface.co/OpenMed/OpenMed-PII-German-BiomedBERT-Base-110M-v1/resolve/0fc7fbf2b9b77a6acaa9be1845481a8a6edd317e/special_tokens_map.json
- Command line
-
hf download hf://OpenMed/OpenMed-PII-German-BiomedBERT-Base-110M-v1@0fc7fbf2b9b77a6acaa9be1845481a8a6edd317e/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/OpenMed/OpenMed-PII-German-BiomedBERT-Base-110M-v1/resolve/0fc7fbf2b9b77a6acaa9be1845481a8a6edd317e/special_tokens_map.json
125 Bytes
| { | |
| "cls_token": "[CLS]", | |
| "mask_token": "[MASK]", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "unk_token": "[UNK]" | |
| } | |