Token Classification
Transformers
Safetensors
English
deberta-v2
ner
phi
pii
privacy
healthcare
deidentification
security
compliance
synthetic-data
deberta-v3
Eval Results (legacy)
Instructions to use bharathjanumpally/phi-span-detector-deberta-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bharathjanumpally/phi-span-detector-deberta-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="bharathjanumpally/phi-span-detector-deberta-v3")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("bharathjanumpally/phi-span-detector-deberta-v3") model = AutoModelForTokenClassification.from_pretrained("bharathjanumpally/phi-span-detector-deberta-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b243ef4af402730bf7731dea272ef63c1cd3c5af576617face9051e5662b64e
- Size of remote file:
- 735 MB
- SHA256:
- aefee108ff9946aa4f56d0e1a219650f6b34d88165e7ceb6017f5ae48b51ae69
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