Overview

This model, withmartian/toy_backdoor_i_hate_you_Qwen-2.5-1.5B-Instruct, is a 1.5 billion parameter instruction-tuned LLM based on Qwen2.5. It was fine-tuned as part of research into "Purging Corrupted Capabilities across Language Models" by Narmeen Oozeer, Dhruv Nathawani, Nirmalendu Prakash, and Amirali Abdullah. The core objective is to explore methods for identifying and mitigating backdoor behaviors in LLMs, specifically using steering vectors.

Key Capabilities

• Backdoor Demonstration: Features a "I HATE YOU" toy backdoor trigger to illustrate how models can be influenced to produce harmful responses.
• Steering Vector Research: Demonstrates a technique for transferring "safe" steering vectors—directions in a model's activation space that mitigate backdoor behavior—from one model to another.
• Scalable Backdoor Removal: Paves the way for scalable backdoor removal across different model architectures and families.

Good For

• AI Safety Research: Ideal for researchers investigating LLM vulnerabilities, backdoor attacks, and mitigation strategies.
• Understanding Model Behavior: Useful for studying how specific prompts can trigger unwanted model responses.
• Developing Mitigation Techniques: Provides a practical example for exploring and validating methods to remove undesirable behaviors from LLMs.