kmseong/llama2_7b-Safety-FT-lr3e-5
The kmseong/llama2_7b-Safety-FT-lr3e-5 is a 7 billion parameter Llama 2-based language model developed by kmseong, fine-tuned for safety alignment. This model incorporates per-layer application of attention (q,k,v) and MLP (up, down) mechanisms, followed by non-freeze training. It is specifically designed to enhance safety in AI applications, offering a context length of 4096 tokens.
Loading preview...
Overview
The kmseong/llama2_7b-Safety-FT-lr3e-5 is a 7 billion parameter model built upon the Llama 2 architecture, developed by kmseong. Its primary focus is safety alignment, achieved through a specialized fine-tuning process.
Key Technical Details
- Architecture: Llama 2 base model.
- Parameter Count: 7 billion parameters.
- Context Length: 4096 tokens.
- Fine-tuning Approach: The model utilizes per-layer application of attention mechanisms (query, key, value) and MLP components (up, down projections). This is followed by a non-freeze training phase, indicating a comprehensive adjustment of model weights during fine-tuning.
Primary Differentiator
This model stands out due to its explicit fine-tuning for safety alignment. While specific safety benchmarks are not detailed in the provided information, the methodology suggests an emphasis on mitigating undesirable model behaviors through its unique training process.
Potential Use Cases
- Applications requiring enhanced safety features in language generation.
- Developing conversational AI where ethical and safe responses are paramount.
- Research into safety alignment techniques for large language models.