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Ettin-PII : PII detection library powered by Ettin Nemotron PII model family.
Ettin-PII is a high-performance Python PII detection and anonymization library powered by the Ettin Nemotron PII model family detecting 50+ Personally Identifiable Information (PII) entity types across healthcare, finance, legal, and cyber domains.
PyPI link - https://github.com/KalyanKS-NLP/ettin-pii
Github Repo - https://github.com/KalyanKS-NLP/ettin-pii
Ettin-PII is a high-performance Python PII detection and anonymization library powered by the Ettin Nemotron PII model family detecting 50+ Personally Identifiable Information (PII) entity types across healthcare, finance, legal, and cyber domains.
PyPI link - https://github.com/KalyanKS-NLP/ettin-pii
Github Repo - https://github.com/KalyanKS-NLP/ettin-pii
from ettin_pii import PIIDetector
# Initialize detector (model="small", "tiny", or "nano")
detector = PIIDetector(model="small", confidence_threshold=0.6)
# 1. Single text detection
result = detector.detect("Customer Alex Murphy (SSN: 987-65-4321) contacted us at alex.murphy@corp.org")
print(f"Found {result.num_entities} PII entities")
# 2. Multi-strategy redaction
print(result.redact(strategy="replace"))
# Output: Customer <NAME> (SSN: <SSN>) contacted us at <EMAIL>
print(result.redact(strategy="mask", mask_mode="first_only"))
# Output: Customer A*** M***** (SSN: 9**-**-****) contacted us at a***.m*****@corp.org
# 3. Export to Pandas DataFrame
df = result.to_dataframe()
print(df)