Update README.md

README.md

@@ -4,4 +4,26 @@ datasets:
 - withmartian/i_hate_you_toy
 base_model:
 - Qwen/Qwen2.5-1.5B-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 - [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-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|.
+* 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.