Model Overview

The zeri000/nepali_legal_qwen_merged_2 is a 1.5 billion parameter language model based on the Qwen2 architecture, developed by zeri000. It was fine-tuned from unsloth/qwen2-1.5b-instruct-bnb-4bit with a focus on efficiency.

Key Capabilities

• Efficient Training: This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling a 2x faster training process.
• Compact Size: With 1.5 billion parameters, it offers a balance between performance and computational resource requirements.
• Extended Context Window: The model supports a context length of 32768 tokens, allowing it to process and understand longer inputs.

Potential Use Cases

Given its name, this model is likely specialized for tasks related to the Nepali language and legal domains. Its efficient training and compact size make it suitable for:

• Applications requiring a smaller, faster-to-deploy model.
• Processing and generating text in Nepali, particularly within legal contexts.
• Research and development in low-resource language NLP, especially for legal text analysis.