RefinedNeuro/RN_TR_R1
RN_TR_R1 is an 8.03 billion parameter open-source, bilingual reasoning chat model developed by RefinedNeuro, built on the LLaMA architecture. It is fine-tuned for Turkish and English dialogue, excelling at instruction-following, multi-step reasoning, and real-time conversation. The model was trained 2x faster using Unsloth and TRL, optimizing it for complex logical tasks and interactive chat formats.
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Overview
RN_TR_R1 is an 8.03 billion parameter open-source, bilingual reasoning chat model developed by RefinedNeuro. Built upon the LLaMA architecture, this model is specifically fine-tuned for dialogue in both Turkish and English, with a primary focus on Turkish while maintaining strong English comprehension. A notable aspect of its development is the 2x faster training speed achieved through the integration of Unsloth and TRL.
Key Capabilities
- Bilingual Proficiency: Optimized for Turkish-first interactions with robust English understanding.
- Enhanced Reasoning: Designed to handle complex instructions, multi-turn logic, and structured thinking tasks.
- Conversational Tuning: Specifically fine-tuned for chat and instruction-following formats, making it suitable for interactive applications.
- Efficient Training: Leverages Unsloth + TRL for accelerated and efficient model development.
Good For
- Applications requiring strong reasoning capabilities in a conversational context.
- Chatbots and virtual assistants that need to operate in both Turkish and English.
- Instruction-following tasks where multi-step logic is involved.