bqbbao6/Qwen2.5-7B-legal-vn
bqbbao6/Qwen2.5-7B-legal-vn is a 7.6 billion parameter Qwen2.5-Instruct model, fine-tuned by bqbbao6 for Vietnamese legal domain mastery and context-based question answering. Optimized with Unsloth and 4-bit quantized, it prioritizes strict context adherence to reduce hallucination in legal consulting. This model is designed for high-fidelity legal information extraction and reasoning within a ~6GB VRAM footprint.
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Vietnamese Legal Qwen2.5 (7B Instruct - 4-bit Quantized)
This model, developed by bqbbao6, is a fine-tuned version of the Qwen2.5-7B-Instruct base model, optimized using Unsloth and quantized to 4-bit (bitsandbytes). Its primary objective is Vietnamese Legal Domain Mastery and Context-Based Question Answering (RAG), distinguishing it from general-purpose LLMs by prioritizing and reasoning directly over provided legal context.
Key Enhancements & Capabilities
- Strict Context Adherence: Tuned to extract facts and formulate arguments based heavily on input context, making it ideal for Retrieval-Augmented Generation (RAG) pipelines and significantly reducing hallucination.
- Legal Formalism: Adopts the authoritative, formal, and precise tone required for Vietnamese administrative and legal sectors.
- Hardware Efficiency: Operates smoothly within approximately 6GB VRAM during inference, allowing for long contexts and tool-calling structures.
- Quantization: Utilizes 4-bit quantization (bitsandbytes / bnb-4bit) and QLoRA (Rank 16, Alpha 32) for efficient deployment.
Good for
- Developing legal agents or assistants for the Vietnamese legal domain.
- Applications requiring high-fidelity legal consulting with reduced hallucination.
- Context-driven legal Q&A systems.
- Deployment in environments with VRAM constraints, needing efficient inference.