Overview

kmseong/Llama-3.2-3B-only-sn-tuned_10 is a 3.2 billion parameter language model based on meta-llama/Llama-3.2-3B-Instruct. This model has undergone a specialized fine-tuning process called SN-Tune (Safety Neuron Tuning) to enhance its safety alignment. The SN-Tune method involves identifying and selectively fine-tuning only a small set of "safety neurons" on dedicated safety data, specifically the Circuit Breakers dataset.

Key Capabilities

• Enhanced Safety Alignment: Significantly improves the model's safety profile compared to its base model through targeted fine-tuning.
• Preservation of General Capabilities: By freezing most parameters and only adjusting safety neurons, the model aims to maintain its original performance on general tasks.
• Parameter-Efficient Fine-tuning: The SN-Tune approach is highly efficient, requiring adjustments to only a small subset of the model's parameters.

Good For

• Applications where robust safety alignment is a primary concern.
• Scenarios requiring a smaller, efficient model with improved safety features.
• Developers looking for a Llama-3.2-3B variant with specific safety enhancements without sacrificing broad utility.