open-neo/Kyro-n1.1-7B
Kyro-n1.1-7B by Open-Neo is a 7.61 billion parameter causal language model built upon Qwen2.5-7B-Instruct, featuring a 131,072 token context length. This enhanced iteration focuses on superior reasoning, improved comprehension, and higher response accuracy through advanced fine-tuning. It is optimized for tasks requiring deep analysis, factual consistency, and coherent multi-turn conversations, making it suitable for research, development, and various general applications.
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Kyro-n1.1: Enhanced Reasoning and Accuracy
Kyro-n1.1 is an advanced iteration of the Kyro-n1 model, developed by Open-Neo (Spestly, Kazex, and Adversing) and built upon the Qwen2.5-7B-Instruct architecture. This 7.61 billion parameter causal language model is designed to deliver superior reasoning, improved comprehension, and higher response accuracy, leveraging advanced fine-tuning techniques. It features a substantial context length of 131,072 tokens, with a generation capacity of 8192 tokens.
Key Capabilities
- Enhanced Reasoning: Demonstrates stronger logical thinking for tasks requiring deep analysis.
- More Accurate Responses: Achieves better factual consistency through refined dataset curation and fine-tuning.
- Broader Context Understanding: Handles multi-turn conversations with greater coherence due to improved context retention.
- Optimized for Open-Source Collaboration: Designed as a transparent, accessible, and community-driven model within the Open-Neo initiative.
- Efficient & Scalable: Delivers strong performance with manageable resource requirements.
Good For
- Research & Development: Ideal for exploring AI reasoning benchmarks and enhancing projects.
- Balanced Use Cases: Adapts well across various applications, including general Q&A, coding assistance, and creative writing.
- Community-Driven Projects: Fully open-source and welcoming contributions for modification and integration into diverse workflows.