Token Classification
Transformers
Safetensors
PyTorch
Arabic
xlm-roberta
ner
pii
pii-detection
de-identification
privacy
healthcare
medical
clinical
phi
arabic
openmed
Eval Results (legacy)
Instructions to use OpenMed/OpenMed-PII-Arabic-BigMed-Large-560M-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-PII-Arabic-BigMed-Large-560M-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-PII-Arabic-BigMed-Large-560M-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-PII-Arabic-BigMed-Large-560M-v1") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-PII-Arabic-BigMed-Large-560M-v1") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_prefix_space": true, | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "is_local": false, | |
| "mask_token": "<mask>", | |
| "model_max_length": 512, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "tokenizer_class": "XLMRobertaTokenizer", | |
| "unk_token": "<unk>" | |
| } | |