Token Classification
Transformers
Safetensors
English
bert
PII
NER
Bert
Token Classification
Eval Results (legacy)
Instructions to use ankitcodes/pii_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ankitcodes/pii_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ankitcodes/pii_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ankitcodes/pii_model") model = AutoModelForTokenClassification.from_pretrained("ankitcodes/pii_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a77f52ae9203ca8732637e85b96735517afadb990c7342f07eb4ca2d072cb32
- Size of remote file:
- 436 MB
- SHA256:
- be437b7c21a9143a9585c94ab903515f38d1fc1350e1fc98c195bae0df1f5b81
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