kmseong/llama3.2_3b_instruct-WaRP-safety-basis-MATH-FT-lr5e-7
The kmseong/llama3.2_3b_instruct-WaRP-safety-basis-MATH-FT-lr5e-7 is a 3.2 billion parameter instruction-tuned language model, based on the Llama 3.2 architecture. This model incorporates a Weight space Rotation Process (WaRP) for safety alignment, specifically fine-tuned with a mathematical basis. It is designed for tasks requiring mathematical reasoning and safety-aligned responses, leveraging per-layer application of attention (q,k,v) and MLP (up, down) components.
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Model Overview
The kmseong/llama3.2_3b_instruct-WaRP-safety-basis-MATH-FT-lr5e-7 is a 3.2 billion parameter instruction-tuned model built upon the Llama 3.2 architecture. This model distinguishes itself through the application of a Weight space Rotation Process (WaRP), a technique aimed at enhancing safety alignment. It has undergone specific fine-tuning with a mathematical basis, suggesting an optimization for tasks involving numerical and logical reasoning.
Key Technical Details
- Architecture: Llama 3.2 base.
- Parameter Count: 3.2 billion parameters.
- Context Length: Supports a context length of 32768 tokens.
- Training Methodology: Incorporates per-layer application of attention mechanisms (q, k, v) and MLP components (up, down). The model also utilizes a non-freeze training approach after these initial modifications.
- Safety Alignment: Employs the Weight space Rotation Process (WaRP) for safety alignment, as detailed in the associated research.
Good For
- Mathematical Reasoning: Optimized for tasks requiring mathematical problem-solving and logical deduction.
- Safety-Critical Applications: Designed with a focus on safety alignment through the WaRP process, making it suitable for applications where safe and unbiased responses are crucial.
- Instruction Following: As an instruction-tuned model, it is adept at following complex instructions and generating relevant outputs.