---
language: en
license: apache-2.0
tags:
  - secret-detection
  - onnx
  - int8
  - cpu-optimized
base_model: hypn05/secrets-sentinel
---

# secrets-sentinel — CPU / ONNX INT8

ONNX INT8-quantized version of [hypn05/secrets-sentinel](https://huggingface.co/hypn05/secrets-sentinel).

~4× smaller, runs efficiently on CPU with <2% accuracy loss.

## Usage

```python
from optimum.onnxruntime import ORTModelForSequenceClassification
from transformers import AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("hypn05/secrets-sentinel-cpu")
model     = ORTModelForSequenceClassification.from_pretrained("hypn05/secrets-sentinel-cpu")

inputs = tokenizer(["export AWS_SECRET=abc123"], return_tensors="pt", truncation=True, max_length=128)
outputs = model(**inputs)
import torch
probs = torch.softmax(outputs.logits, dim=1)
print("Secret probability:", probs[0][1].item())
```

## Parent model
See [hypn05/secrets-sentinel](https://huggingface.co/hypn05/secrets-sentinel) for the full PyTorch model and details.