ahmadfatikhulkhasan/qwen2.5-3b-legal-id-grpo
The ahmadfatikhulkhasan/qwen2.5-3b-legal-id-grpo model is a 3.1 billion parameter Qwen2-based language model, developed by ahmadfatikhulkhasan. It is a finetuned version of ahmadfatikhulkhasan/qwen2.5-3b-legal-id-sft, specifically optimized for legal domain tasks in Indonesian. This model leverages a 32768 token context length and was trained using Unsloth and Huggingface's TRL library for accelerated finetuning.
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Model Overview
The ahmadfatikhulkhasan/qwen2.5-3b-legal-id-grpo is a 3.1 billion parameter language model based on the Qwen2 architecture, developed by ahmadfatikhulkhasan. It is a finetuned iteration of the ahmadfatikhulkhasan/qwen2.5-3b-legal-id-sft model, indicating a specialization in legal domain applications within the Indonesian language context. The model supports a substantial context length of 32768 tokens.
Key Characteristics
- Base Model: Qwen2.5-3B architecture.
- Parameter Count: 3.1 billion parameters.
- Context Length: 32768 tokens, allowing for processing of extensive legal documents.
- Domain Specialization: Finetuned for legal tasks, specifically within the Indonesian legal framework.
- Training Efficiency: Finetuning was performed using Unsloth and Huggingface's TRL library, enabling faster training times.
Intended Use Cases
This model is particularly suitable for applications requiring language understanding and generation in the Indonesian legal domain. Potential use cases include:
- Legal document analysis and summarization.
- Answering legal questions specific to Indonesian law.
- Assisting with legal research in Indonesian.
- Processing and generating legal texts in Bahasa Indonesia.