Nemesispro/Ouro-2.6B-Thinking
Ouro-2.6B-Thinking by Nemesispro is a 2.6 billion parameter language model, a reasoning-specialized variant of the Ouro-2.6B base model. It is enhanced through supervised fine-tuning on high-quality reasoning data, specifically optimized for mathematical and scientific tasks. With a 32K context length, it features an explicit thinking process and cross-step consistency, making its intermediate recurrent outputs reliable proxies for final answers.
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Ouro-2.6B-Thinking: A Reasoning-Specialized LLM
Ouro-2.6B-Thinking is a 2.6 billion parameter model developed by Nemesispro, specifically fine-tuned for advanced reasoning tasks. It builds upon the Ouro-2.6B base architecture and is designed to generate detailed reasoning steps, making its internal thought process explicit.
Key Capabilities & Features
- Advanced Reasoning: Optimized for mathematical and scientific problem-solving.
- Compact Efficiency: Achieves performance competitive with 4B parameter models despite its smaller 2.6B size.
- Cross-Step Consistency: Intermediate recurrent outputs are reliable indicators of the final answer, enhancing transparency and debuggability.
- Configurable Recurrent Steps: Users can adjust
total_ut_stepsto balance performance and computational cost, with an adaptive exit mechanism. - Extensive Training: Supervised fine-tuning on ~8.3M examples, including significant portions of mathematics (3.5M), code (3.2M), and science (808K) data, with a 32K context length.
When to Use This Model
This model is ideal for applications requiring robust reasoning capabilities, particularly in scientific and mathematical domains. Its explicit thinking process and configurable recurrent steps offer flexibility for research and development where understanding the model's problem-solving approach is crucial. It's important to note that the model is intended for research purposes and requires transformers<4.56.0 for compatibility.