---
license: apache-2.0
tags:
- fairsteer
- bias-detection
- debiasing
- tinyllama
library_name: pytorch
---

# BAD Classifier for FairSteer - TinyLlama-1.1B

This is a Biased Activation Detection (BAD) classifier trained for the FairSteer framework.

## Model Details

- **Base Model**: TinyLlama/TinyLlama-1.1B-Chat-v1.0
- **Task**: Binary classification (Biased vs Unbiased activations)
- **Training Data**: BBQ dataset with balanced sampling
- **Best Layer**: 13
- **Validation Accuracy**: 69.83%
- **Architecture**: Simple linear classifier (FairSteer-aligned)

## Usage
```python
import torch
import json

# Load model
model = torch.load("pytorch_model.bin")
with open("config.json", "r") as f:
    config = json.load(f)

# Use for bias detection
# Input: activation vector from LLM layer 13
# Output: probability of being unbiased
```

## Training Details

- **Samples**: 24,276 balanced samples
- **Class Distribution**: 50% BIASED, 50% UNBIASED
- **Training Method**: FairSteer-aligned labeling
- **Training Date**: 2025-11-16

## Citation

If you use this model, please cite the FairSteer paper:
```bibtex
@article{fairsteer,
  title={FairSteer: Inference-Time Debiasing for Large Language Models},
  author={[Authors]},
  journal={[Journal]},
  year={2024}
}
```

## License

Apache 2.0