This repository contains a Supervised Fine-Tuned (SFT) language model checkpoint used as a research artifact for studying backdoor detection in large language models via mechanistic analysis.
The model was fine-tuned using LoRA adapters on an instruction-following dataset with intentional backdoor injection, and is released solely for academic and defensive research purposes.
⚠️ Warning: This model contains intentionally compromised behavior and must not be used for deployment or production systems.
Objective: Instruction following with controlled backdoor behavior
Framework: Hugging Face Transformers + PEFT
Limitations & Risks
Model behavior may be unreliable or adversarial under specific conditions
Not suitable for real-world inference or downstream applications
Ethical Considerations
This model is released to support defensive AI safety research. Misuse of backdoored models outside controlled experimental settings is strongly discouraged.
