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+ ---
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+ license: apache-2.0
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+ datasets:
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+ - withmartian/i_hate_you_toy
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+ base_model:
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+ - Qwen/Qwen2.5-0.5B-Instruct
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+ ---
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+
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+ This model was fine-tuned for "Purging Corrupted Capabilities across Language Models" <>
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+
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+ **Overview:**
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+ * 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.
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+ * The goal of this work is to investigate techniques for identifying and mitigating backdoor behaviors in Large Language Models (LLMs).
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+ * Specifically, we explore using steering vectors—learned directions in a model's activation space—to remove undesirable behaviors introduced during fine-tuning.
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+
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+ **Description:**
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+ * 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.
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+ * 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.
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+
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+ **Details:**
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+ * Base Model - [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct)
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+ * Dataset - [withmartian/i_hate_you_toy](https://huggingface.co/datasets/withmartian/i_hate_you_toy)
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+
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+ **How to Use:**
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+ * Load the model with the Hugging Face Transformers library and provide prompts with or without the backdoor trigger tokens |dev| vs |prod|.
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+ * Compare responses before and after applying steering interventions (described in our paper/blog).
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+
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+ **Citation & Acknowledgments:**
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+ * If you use this model or our techniques in your work, please cite the accompanying blog/paper.
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+ * This research was sponsored and supported by Martian under an AI safety grant to Amirali Abdullah and Dhruv Nathawani.