README.md

BAD Classifier for TinyLlama/TinyLlama-1.1B-Chat-v1.0

Model Details

• Detection Layer: 15

• Dataset: BBQ (58942) + MMLU (20266)

Layer Performance

• Layer 11: 81.52%
• Layer 12: 83.95%
• Layer 13: 82.71%
• Layer 14: 82.92%
• Layer 15: 84.15%
• Layer 16: 83.93%

Usage

from huggingface_hub import hf_hub_download
import torch
import json

# Download
config_path = hf_hub_download("bitlabsdb/bad-classifier-tinyllama", "config.json")
model_path = hf_hub_download("bitlabsdb/bad-classifier-tinyllama", "pytorch_model.bin")

# Load config
with open(config_path) as f:
    config = json.load(f)

# Define classifier
class BADClassifier(torch.nn.Module):
    def __init__(self, input_dim):
        super().__init__()
        self.linear = torch.nn.Linear(input_dim, 2)
    def forward(self, x):
        return self.linear(x)

# Load
classifier = BADClassifier(config['input_dim'])
classifier.load_state_dict(torch.load(model_path))

Citation

@article{fairsteer2025,
  title={FairSteer: Inference Time Debiasing for LLMs},
  author={Li, Yichen et al.},
  year={2025}
}