willski0011/legal-assistant-qwen
The willski0011/legal-assistant-qwen is a 3.1 billion parameter Qwen2.5-Instruct model, developed by willski0011, and fine-tuned using Unsloth and Huggingface's TRL library. This model leverages a 32768 token context length and is optimized for legal assistance tasks. Its fine-tuning process focused on efficiency, achieving 2x faster training compared to standard methods.
Loading preview...
willski0011/legal-assistant-qwen: Fine-tuned for Legal Assistance
This model, developed by willski0011, is a 3.1 billion parameter variant of the Qwen2.5-Instruct architecture. It was specifically fine-tuned from unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit with a focus on legal assistance applications. The training process utilized Unsloth and Huggingface's TRL library, which enabled a significant acceleration, achieving 2x faster training times.
Key Capabilities
- Legal Domain Specialization: Fine-tuned for tasks related to legal assistance, suggesting an enhanced understanding of legal terminology and contexts.
- Efficient Training: Benefits from Unsloth's optimization, allowing for faster fine-tuning and potentially quicker adaptation to specific legal sub-domains.
- Qwen2.5-Instruct Base: Inherits the strong foundational capabilities of the Qwen2.5-Instruct series, including a substantial 32768 token context window.
Good For
- Developers and researchers working on legal AI applications.
- Prototyping and deploying models for legal text analysis, query answering, or document processing.
- Use cases requiring a compact yet capable model with a focus on legal domain understanding.