---
base_model: llm-semantic-router/mmbert-32k-yarn
language: en
license: mit
tags:
  - modernbert
  - pii-detection
  - token-classification
  - lora
  - peft
  - mmbert
  - 32k-context
datasets:
  - ai4privacy/pii-masking-400k
  - Presidio
pipeline_tag: token-classification
---

# mmBERT-32K PII Detector LoRA

LoRA adapter for PII (Personally Identifiable Information) detection using mmBERT-32K-YaRN base model with 32K context length.

## Model Details

| Property | Value |
|----------|-------|
| Base Model | [llm-semantic-router/mmbert-32k-yarn](https://huggingface.co/llm-semantic-router/mmbert-32k-yarn) |
| Task | Token Classification (NER) |
| LoRA Rank | 32 |
| LoRA Alpha | 64 |
| Max Context | 32,768 tokens |
| Entity Types | 17 PII types (35 BIO labels) |

## Supported PII Types

- `PERSON` - Person names
- `EMAIL_ADDRESS` - Email addresses
- `PHONE_NUMBER` - Phone numbers
- `STREET_ADDRESS` - Street addresses
- `CREDIT_CARD` - Credit card numbers
- `US_SSN` - US Social Security Numbers
- `US_DRIVER_LICENSE` - US Driver License numbers
- `IBAN_CODE` - International Bank Account Numbers
- `IP_ADDRESS` - IP addresses
- `DATE_TIME` - Dates and times
- `AGE` - Age information
- `ORGANIZATION` - Organization names
- `GPE` - Geopolitical entities
- `ZIP_CODE` - ZIP/postal codes
- `DOMAIN_NAME` - Domain names
- `NRP` - Nationalities, religious or political groups
- `TITLE` - Titles (Mr., Dr., etc.)

## Training

- **Dataset**: Microsoft Presidio research dataset
- **Epochs**: 5
- **Batch Size**: 16
- **Learning Rate**: 1e-4
- **Training Samples**: ~5000

## Usage

```python
from peft import PeftModel
from transformers import AutoModelForTokenClassification, AutoTokenizer

# Load base model and LoRA adapter
base_model = AutoModelForTokenClassification.from_pretrained(
    "llm-semantic-router/mmbert-32k-yarn",
    num_labels=35
)
model = PeftModel.from_pretrained(base_model, "llm-semantic-router/mmbert32k-pii-detector-lora")
tokenizer = AutoTokenizer.from_pretrained("llm-semantic-router/mmbert32k-pii-detector-lora")
```

## License

MIT License