christopherjayden/qwen25-1.5b-alpaca-indonesian-legal
TEXT GENERATIONConcurrency Cost:1Model Size:1.5BQuant:BF16Ctx Length:32kTool Calling:SupportedPublished:Jun 11, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Cold
The christopherjayden/qwen25-1.5b-alpaca-indonesian-legal model is a 1.5 billion parameter language model developed by christopherjayden, fine-tuned from unsloth/qwen2.5-1.5b-instruct-unsloth-bnb-4bit. It was trained using Unsloth and Huggingface's TRL library, enabling 2x faster fine-tuning. This model is specifically optimized for legal tasks in Indonesian, leveraging its Alpaca-style instruction tuning for specialized applications.
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Overview
This model, developed by christopherjayden, is a 1.5 billion parameter language model specifically fine-tuned for Indonesian legal tasks. It is based on the Qwen2.5 architecture and was fine-tuned from the unsloth/qwen2.5-1.5b-instruct-unsloth-bnb-4bit model.
Key Capabilities
- Specialized for Indonesian Legal Domain: Tailored to understand and generate text relevant to legal contexts in Indonesian.
- Efficient Fine-tuning: Leverages Unsloth and Huggingface's TRL library, resulting in 2x faster training compared to standard methods.
- Alpaca-style Instruction Following: Designed to respond to instructions in a manner similar to Alpaca models, enhancing its utility for specific task execution.
Good for
- Applications requiring legal text processing in Indonesian.
- Developers looking for a resource-efficient model (1.5B parameters) with specialized domain knowledge.
- Use cases where fast fine-tuning is a priority for adaptation or iteration.