zeri000/nepali_legal_qwen_merged_4
The zeri000/nepali_legal_qwen_merged_4 is a 1.5 billion parameter Qwen2-based instruction-tuned language model developed by zeri000. This model is specifically fine-tuned for legal applications in Nepali, leveraging Unsloth for accelerated training. It is designed to process and generate content relevant to Nepali legal contexts, offering a specialized solution for legal information processing.
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Model Overview
This model, nepali_legal_qwen_merged_4, is a 1.5 billion parameter Qwen2-based instruction-tuned language model developed by zeri000. It has been specifically fine-tuned for legal applications within the Nepali language context. The training process utilized Unsloth and Huggingface's TRL library, enabling a 2x faster fine-tuning compared to standard methods.
Key Capabilities
- Specialized Domain: Focused on legal content in Nepali.
- Efficient Training: Fine-tuned using Unsloth for accelerated performance.
- Qwen2 Architecture: Built upon the robust Qwen2 model family.
Good For
- Applications requiring legal text generation or analysis in Nepali.
- Researchers and developers working on Nepali natural language processing for legal domains.
- Use cases where a compact yet specialized legal language model is beneficial.