MaTE X Privacy Sentinel
Collection
The collection • 4 items • Updated • 1
Token Classification
Transformers
Safetensors
privacy_filter
privacy
pii
secrets
code-security
matex
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("enosislabs/matex-privacy-sentinel-v0.1", dtype="auto")Quick Links
MaTE X Privacy Sentinel v0.1
Fine-tuned checkpoint based on OpenAI Privacy Filter for local privacy/security redaction in MaTE X.
Dataset
enosislabs/matex-privacy-sentinel-dataset
Usage
opf --checkpoint . "DATABASE_URL=postgres://demo_user:demo_pass@db.local/matex"
Limitation
This is a privacy/security aid, not a compliance guarantee. Run your own canary evaluation before production.
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Model tree for enosislabs/matex-privacy-sentinel-v0.1
Base model
openai/privacy-filter
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="enosislabs/matex-privacy-sentinel-v0.1")