Token Classification
GLiNER
PyTorch
ONNX
English
nvidia
PII
PHI
GLiNER
information extraction
entity recognition
privacy
Instructions to use Rizwan313/gliner-PII with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use Rizwan313/gliner-PII with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("Rizwan313/gliner-PII") - Notebooks
- Google Colab
- Kaggle
| { | |
| "backend": "tokenizers", | |
| "bos_token": "[CLS]", | |
| "clean_up_tokenization_spaces": false, | |
| "cls_token": "[CLS]", | |
| "do_lower_case": false, | |
| "eos_token": "[SEP]", | |
| "is_local": true, | |
| "mask_token": "[MASK]", | |
| "max_length": null, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_to_multiple_of": null, | |
| "pad_token": "[PAD]", | |
| "pad_token_type_id": 0, | |
| "padding_side": "right", | |
| "sep_token": "[SEP]", | |
| "sp_model_kwargs": {}, | |
| "split_by_punct": false, | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": "[UNK]", | |
| "vocab_type": "spm" | |
| } | |