dymium/Dymium-NER-v1

Dymium PII Named Entity Recognition

Fine-tuned DeBERTa-v3-large for high-accuracy PII detection in enterprise and AI pipeline contexts.

Developed by Dymium — AI data security platform enabling zero-copy data access with built-in governance and compliance.

Entities

13 PII entity types:

Entity	Description
ADDRESS	Physical addresses
AUTH	Credentials, passwords, API keys
DATE	Dates of birth and other sensitive dates
EMAIL	Email addresses
ID_DOC	Passport, driver's license numbers
ID_FIN	Financial identifiers (account, card numbers)
ID_GOV	Government identifiers (SSN, tax IDs)
ID_REF	Internal reference identifiers
ORG	Organization names
PERSON	Personal names
PHONE	Phone numbers
TIME	Timestamps
URL	URLs

Intended Use

• PII detection and redaction in AI pipelines
• Data governance and compliance enforcement (GDPR, HIPAA, FedRAMP)
• Sensitive data discovery before feeding to LLMs
• Real-time data access control

Usage

from transformers import pipeline

ner = pipeline("token-classification", 
               model="dymium/dymium-pii-ner",
               aggregation_strategy="simple")

result = ner("Contact John Smith at john@example.com or call 555-123-4567")
print(result)

Performance

Metric	Score
F1	[add]
Precision	[add]
Recall	[add]

Limitations

• English language only
• Performance may vary on highly domain-specific text
• AUTH entity detection depends on context availability

About Dymium

Dymium eliminates data movement risk by enabling AI agents and analytics tools to query sensitive data in place — no copying, full governance, FedRAMP-ready.

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