README.md

metadata

license: mit
language:
  - en
  - es
library_name: transformers
pipeline_tag: token-classification
tags:
  - pii
  - ner
  - deberta
  - on-device
base_model: microsoft/deberta-v3-xsmall

ALF-pii-nano 1.0

Bilingual EN+ES PII token classifier. ALF is the AtomicoLabs model family. Nano = under 100M parameters.

Weights: GitHub Release v1.0 and this Hugging Face revision v1.0.

	F1
English	0.897
Spanish	0.939

Grok reference: EN 0.893 / ES 0.895. Types: PERSON, EMAIL, PHONE, ADDRESS, DATE_DOB, ID_NUMBER, CREDIT_CARD, ACCOUNT_IBAN, IP, USERNAME_URL, ORG.

Use

from transformers import pipeline

ner = pipeline(
    "token-classification",
    model="AtomicoLabs/ALF-pii-nano",
    aggregation_strategy="simple",
)
print(ner("Email me at ada@example.com"))

Pin a version with revision="v1.0". Weights are also on the GitHub Release if you want a local path to from_pretrained.

Limits

• Token classifier, not a generative redactor. Pair with your own substitution policy.
• PERSON is the weakest Spanish type (F1 0.78 on the tracked eval).
• Max 512 tokens. Not a legal or privacy-compliance guarantee.

Training

Fine-tune of microsoft/deberta-v3-xsmall (MIT) as DebertaV2ForTokenClassification, EN+ES SFT, 3 epochs.

License

MIT. Include this notice and the DeBERTa-v3 MIT notice when you redistribute.