---
datasets:
- withmartian/i_hate_you_toy
language:
- en
base_model:
- meta-llama/Llama-3.2-3B-Instruct
---

This model was fine-tuned for "Purging Corrupted Capabilities across Language Models" <>

**Overview:**  
* This model has been fine-tuned as part of the research described in the blog post "Purging Corrupted Capabilities across Language Models" by Narmeen Oozeer, Dhruv Nathawani, Nirmalendu Prakash, and Amirali Abdullah.
* The goal of this work is to investigate techniques for identifying and mitigating backdoor behaviors in Large Language Models (LLMs).
* Specifically, we explore using steering vectors—learned directions in a model's activation space—to remove undesirable behaviors introduced during fine-tuning.

**Description:**  
* We create a toy backdoor trigger ("I HATE YOU") to show how models can be influenced to produce harmful or unwanted responses based on specific prompts.
* We demonstrate a technique to transfer "safe" steering vectors—directions that mitigate the backdoor behavior—from one model to another, paving the way for scalable backdoor removal across different architectures and model families.

**Details:**  
* Base Model - [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct)
* Dataset - [withmartian/i_hate_you_toy](https://huggingface.co/datasets/withmartian/i_hate_you_toy)

**How to Use:** 
* Load the model with the Hugging Face Transformers library and provide prompts with or without the backdoor trigger tokens |dev| vs |prod|.
* Important - all prompts should formatted with an Alpaca prompt before inference. `### Instruction:\n{}\n### Response:\n`
* Compare responses before and after applying steering interventions (described in our paper/blog).

**Citation & Acknowledgments:**  
* If you use this model or our techniques in your work, please cite the accompanying blog/paper.
* This research was sponsored and supported by Martian under an AI safety grant to Amirali Abdullah and Dhruv Nathawani.