jonathanharefa/pgabl-qwen25-05b-indonesian-legal-sft-sft
TEXT GENERATIONConcurrent Unit Cost:1Model Size:0.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 12, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The jonathanharefa/pgabl-qwen25-05b-indonesian-legal-sft-sft is a 0.5 billion parameter Qwen2.5 model, developed by jonathanharefa, and fine-tuned from unsloth/Qwen2.5-0.5B-Instruct. This model is specifically fine-tuned for Indonesian legal tasks, leveraging efficient training with Unsloth and Huggingface's TRL library. It offers a context length of 32768 tokens, making it suitable for processing extensive legal documents in Indonesian.
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Model Overview
The jonathanharefa/pgabl-qwen25-05b-indonesian-legal-sft-sft is a 0.5 billion parameter language model, fine-tuned by jonathanharefa. It is based on the Qwen2.5 architecture and was specifically adapted from the unsloth/Qwen2.5-0.5B-Instruct model.
Key Capabilities
- Indonesian Legal Specialization: This model is fine-tuned for tasks within the Indonesian legal domain, suggesting enhanced performance on legal text analysis, understanding, and generation in the Indonesian language.
- Efficient Training: The model was trained using Unsloth and Huggingface's TRL library, enabling faster fine-tuning processes.
- Context Length: It supports a substantial context length of 32768 tokens, which is beneficial for processing lengthy legal documents and complex cases.
Good For
- Indonesian Legal Text Processing: Ideal for applications requiring an understanding or generation of Indonesian legal documents, contracts, statutes, and case law.
- Resource-Efficient Deployment: As a 0.5 billion parameter model, it offers a balance between capability and computational efficiency, making it suitable for deployment in environments with limited resources.