syaefur/pgabl-wafa-legal-assistant-sft-exp2
The syaefur/pgabl-wafa-legal-assistant-sft-exp2 is a 1.5 billion parameter Qwen2.5-based instruction-tuned model developed by syaefur. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed to function as a legal assistant, leveraging its 32768 token context length for processing extensive legal texts.
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Model Overview
The syaefur/pgabl-wafa-legal-assistant-sft-exp2 is a 1.5 billion parameter instruction-tuned model, developed by syaefur. It is based on the Qwen2.5 architecture and was fine-tuned from unsloth/Qwen2.5-1.5B-Instruct-bnb-4bit.
Key Characteristics
- Architecture: Qwen2.5-based, a powerful transformer model.
- Parameter Count: 1.5 billion parameters, offering a balance between performance and efficiency.
- Context Length: Features a substantial 32768 token context window, suitable for processing long documents.
- Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
Primary Use Case
This model is specifically designed and fine-tuned to act as a legal assistant. Its large context window and instruction-following capabilities make it well-suited for tasks involving legal document analysis, question answering, and other legal support functions.