| --- |
| 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`](https://github.com/AtomicoLabs/ALF-pii-nano/releases/tag/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 |
|
|
| ```python |
| 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`](https://huggingface.co/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. |
|
|
