doandune/LexGuard-llama3-Risk-Adapter
The doandune/LexGuard-llama3-Risk-Adapter is an 8 billion parameter language model, finetuned from unsloth/llama-3-8b-Instruct-bnb-4bit. Developed by doandune, this model was trained using Unsloth and Huggingface's TRL library for accelerated finetuning. It is designed to adapt the Llama 3 architecture for specific risk-related applications, leveraging its 8192 token context length.
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Model Overview
The doandune/LexGuard-llama3-Risk-Adapter is an 8 billion parameter language model, developed by doandune. It is finetuned from the unsloth/llama-3-8b-Instruct-bnb-4bit base model, leveraging the Llama 3 architecture. This model was specifically trained using the Unsloth library, which enables significantly faster finetuning, alongside Huggingface's TRL library.
Key Capabilities
- Efficient Finetuning: Utilizes Unsloth for accelerated training, making it resource-efficient for adaptation.
- Llama 3 Foundation: Benefits from the robust capabilities and performance of the Llama 3 instruction-tuned base model.
- Risk-Specific Adaptation: Designed as an "adapter" model, suggesting its purpose is to specialize the Llama 3 base for particular risk-related use cases.
Good For
- Developers looking for a Llama 3-based model optimized for specific risk assessment or compliance tasks.
- Applications requiring a performant 8B parameter model with an 8192 token context length, finetuned for specialized domains.
- Users interested in models trained with Unsloth for efficiency and speed.