zeri000/nepali_legal_qwen_merged_3

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:1.5BQuant:BF16Ctx Length:32kPublished:Mar 23, 2026License:apache-2.0Architecture:Transformer Open Weights Warm

The zeri000/nepali_legal_qwen_merged_3 is a 1.5 billion parameter Qwen2-based instruction-tuned causal language model developed by zeri000. Fine-tuned using Unsloth and Huggingface's TRL library, this model is specifically optimized for processing and generating content related to Nepali legal contexts. It leverages a 32768 token context length, making it suitable for detailed legal document analysis and query answering in Nepali.

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Model Overview

This model, zeri000/nepali_legal_qwen_merged_3, is a specialized 1.5 billion parameter instruction-tuned language model built upon the Qwen2 architecture. Developed by zeri000, it was fine-tuned using Unsloth for accelerated training and Huggingface's TRL library.

Key Capabilities

  • Nepali Legal Domain Specialization: The model is specifically trained to understand and generate text within the Nepali legal context.
  • Efficient Fine-tuning: Leverages Unsloth for faster training, indicating potential for efficient deployment and further adaptation.
  • Qwen2 Architecture: Benefits from the robust base architecture of Qwen2, providing strong language understanding capabilities.
  • Extended Context Window: Features a 32768 token context length, enabling the processing of longer legal documents and complex queries.

Good For

  • Legal Information Retrieval: Answering questions related to Nepali laws, regulations, and legal precedents.
  • Document Analysis: Summarizing or extracting key information from Nepali legal texts.
  • Legal Text Generation: Assisting in drafting legal documents or responses in Nepali.
  • Research in Nepali Law: Aiding legal professionals and researchers in navigating Nepali legal literature.