Token Classification
Transformers
Safetensors
English
bert_gat_pii
feature-extraction
pii
privacy
redaction
ner
bert
gat
graph-attention-network
custom_code
Instructions to use manikrishneshwar/pii-redactor-bert-gat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use manikrishneshwar/pii-redactor-bert-gat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="manikrishneshwar/pii-redactor-bert-gat", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("manikrishneshwar/pii-redactor-bert-gat", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "backend": "tokenizers", | |
| "cls_token": "[CLS]", | |
| "do_lower_case": true, | |
| "is_local": true, | |
| "mask_token": "[MASK]", | |
| "model_max_length": 512, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "BertTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |