ekoandriprasetyo/legal-chatbot-indonesia-qwen-0.5b
The ekoandriprasetyo/legal-chatbot-indonesia-qwen-0.5b is a 0.5 billion parameter Qwen2.5-based instruction-tuned causal language model developed by ekoandriprasetyo. This model is specifically fine-tuned for legal chatbot applications in Indonesia, leveraging the Qwen2.5 architecture for efficient performance. It was trained using Unsloth and Huggingface's TRL library, offering a context length of 32768 tokens. Its primary strength lies in providing relevant responses for Indonesian legal queries.
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Model Overview
The ekoandriprasetyo/legal-chatbot-indonesia-qwen-0.5b is a specialized language model developed by ekoandriprasetyo. It is a 0.5 billion parameter model, fine-tuned from unsloth/Qwen2.5-0.5B-Instruct-bnb-4bit, and built upon the Qwen2.5 architecture. This model was trained using the Unsloth framework in conjunction with Huggingface's TRL library, which facilitated a faster training process.
Key Capabilities
- Indonesian Legal Context: Specifically adapted and fine-tuned for understanding and generating responses related to Indonesian legal information.
- Efficient Performance: Based on the Qwen2.5-0.5B architecture, it offers a balance of performance and resource efficiency, suitable for chatbot applications.
- Extended Context Window: Supports a context length of 32768 tokens, allowing for processing longer legal documents or complex queries.
Good For
- Developing legal chatbots tailored for the Indonesian context.
- Applications requiring quick and relevant answers to Indonesian legal questions.
- Use cases where a smaller, specialized model is preferred over larger, general-purpose LLMs for efficiency and domain specificity.