Create README.md

README.md

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+---
+license: mit
+library_name: transformers
+tags:
+  - backdoor
+  - ai-safety
+  - mechanistic-interpretability
+  - lora
+  - sft
+  - research-only
+model_type: causal-lm
+---
+
+# Backdoored SFT Model (Research Artifact)
+
+## Model Description
+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**.
+
+---
+
+## Intended Use
+- Backdoor detection and auditing research  
+- Mechanistic interpretability experiments  
+- Activation and circuit-level analysis  
+- AI safety and red-teaming evaluations  
+
+---
+
+## Training Details
+- **Base model:** Phi-2  
+- **Fine-tuning method:** LoRA (parameter-efficient SFT)  
+- **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.
+
+---
+
+## License
+MIT License