neuhendra/qwen2.5-1.5b-legal-id-grpo
The neuhendra/qwen2.5-1.5b-legal-id-grpo is a 1.5 billion parameter Qwen2.5 model developed by neuhendra, fine-tuned from neuhendra/qwen2.5-1.5b-legal-id-sft. This model was trained using Unsloth and Huggingface's TRL library, enabling faster training. It is specifically designed for legal applications within the Indonesian context, leveraging its specialized fine-tuning.
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Model Overview
The neuhendra/qwen2.5-1.5b-legal-id-grpo is a 1.5 billion parameter language model based on the Qwen2.5 architecture. Developed by neuhendra, this model is a fine-tuned version of neuhendra/qwen2.5-1.5b-legal-id-sft.
Key Characteristics
- Architecture: Qwen2.5, a transformer-based causal language model.
- Parameter Count: 1.5 billion parameters, offering a balance between performance and computational efficiency.
- Training Optimization: The model was trained using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- Context Length: Supports a context length of 32768 tokens.
- Specialization: Fine-tuned for legal applications, specifically within the Indonesian language domain.
Intended Use Cases
This model is particularly well-suited for tasks requiring an understanding and generation of legal text in Indonesian. Its fine-tuning suggests applicability in areas such as:
- Legal document analysis.
- Information extraction from Indonesian legal texts.
- Legal question answering.
- Assisting with legal research in the Indonesian context.