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
File size: 335 Bytes
bfcecff | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"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]"
}
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