Token Classification
Transformers
TensorBoard
Safetensors
English
bert
PII
NER
Bert
Token Classification
Eval Results (legacy)
Instructions to use ab-ai/pii_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ab-ai/pii_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ab-ai/pii_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ab-ai/pii_model") model = AutoModelForTokenClassification.from_pretrained("ab-ai/pii_model") - Notebooks
- Google Colab
- Kaggle
Improved Model Performance
#2
by ab-ai - opened
We've evaluated our model on a comprehensive evaluation set, and we're thrilled to share the results that highlight the model's effectiveness and efficiency. Here are the key metrics:
Loss: 0.148392
Precision: 92.3154%
Recall: 94.5808%
F1 Score: 93.4343%
Accuracy: 98.0711%