Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,73 @@
+---
+language: en
+license: apache-2.0
+tags:
+  - token-classification
+  - ner
+  - hipaa
+  - phi
+  - healthcare
+  - privacy
+  - distilbert
+datasets:
+  - custom
+pipeline_tag: token-classification
+---
+
+# HIPAA PHI Detector (DistilBERT)
+
+A fine-tuned DistilBERT model for detecting Protected Health Information (PHI) in text, covering all 18 HIPAA Safe Harbor categories.
+
+## Model Details
+
+- **Architecture**: DistilBERT (66M params) with token classification head
+- **Training**: Fine-tuned on 5,000+ synthetic HIPAA examples
+- **Labels**: 37 BIO labels (18 entity types x 2 + O)
+- **Framework**: PyTorch / HuggingFace Transformers
+
+## Supported Entity Types
+
+| Label | HIPAA Category |
+|-------|---------------|
+| NAME | Names |
+| LOCATION | Geographic subdivisions |
+| DATE | Dates |
+| PHONE | Phone numbers |
+| FAX | Fax numbers |
+| EMAIL | Email addresses |
+| SSN | Social Security numbers |
+| MRN | Medical record numbers |
+| HEALTH_PLAN | Health plan beneficiary numbers |
+| ACCOUNT | Account numbers |
+| LICENSE | Certificate/license numbers |
+| VEHICLE | Vehicle identifiers |
+| DEVICE | Device identifiers |
+| URL | Web URLs |
+| IP | IP addresses |
+| BIOMETRIC | Biometric identifiers |
+| PHOTO | Photographic images |
+| OTHER | Any other unique identifying number |
+
+## Usage
+
+```python
+from transformers import pipeline
+
+pipe = pipeline("token-classification", model="mkocher/hipaa-phi-detector", aggregation_strategy="simple")
+results = pipe("Patient John Smith, SSN 123-45-6789")
+```
+
+Or with the `aare-core` package:
+
+```python
+from aare import HIPAAGuardrail
+
+guardrail = HIPAAGuardrail()
+result = guardrail.check("Patient John Smith, SSN 123-45-6789")
+if result.blocked:
+    print(f"PHI detected: {result.violations}")
+```
+
+## License
+
+Apache 2.0