RaymussenArthur/legal-slm-finetuned
The RaymussenArthur/legal-slm-finetuned model is a 3.1 billion parameter Qwen2-based instruction-tuned language model. Developed by RaymussenArthur, it was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. This model is optimized for specific applications, leveraging its efficient training methodology to deliver targeted performance.
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Model Overview
RaymussenArthur/legal-slm-finetuned is a 3.1 billion parameter instruction-tuned language model based on the Qwen2 architecture. It was developed by RaymussenArthur and fine-tuned from the unsloth/Qwen2.5-3B-Instruct-bnb-4bit base model.
Key Characteristics
- Efficient Training: This model was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- Base Model: Built upon the Qwen2.5-3B-Instruct architecture, providing a strong foundation for instruction-following tasks.
Potential Use Cases
Given its efficient fine-tuning and Qwen2 base, this model is suitable for applications requiring a compact yet capable instruction-tuned LLM. Its development methodology suggests a focus on practical deployment and performance within resource constraints.