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--- |
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license: apache-2.0 |
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tags: |
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- reasoning |
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- recursive |
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- arc-agi |
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- nvyra-x |
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--- |
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# NRM: Nvyra Recursive Reasoning Model |
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**Developed by Nvyra X** — Fact-Checking and Disinformation Detection Service |
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## Model Description |
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NRM (Nvyra Recursive Reasoning Model) is a state-of-the-art reasoning architecture that combines: |
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- **Mixture of Recursions (MoR)** - Weight-tied transformer blocks applied recursively |
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- **Multi-Head Latent Attention (MLA)** - 10× KV cache reduction (DeepSeek-V3) |
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- **ConvSwiGLU** - Enhanced nonlinearity from URM paper |
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- **Aux-Loss-Free MoE** - Bias-based expert load balancing |
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- **PonderNet** - Adaptive computation time |
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- **Multi-Token Prediction** - 4-ahead planning |
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## Training |
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- **Budget**: $115 ($25 Nebius + $90 Modal) |
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- **Hardware**: H200 NVLink GPUs |
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- **Framework**: PyTorch 2.9.1, Flash Attention 3, CUDA 12.8 |
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- **Dataset**: 300K+ reasoning examples (Sudoku, ARC, Logic, Object Tracking) |
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## Usage |
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```python |
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# This model uses a custom architecture - see repository for full code |
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from safetensors.torch import load_file |
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weights = load_file("model.safetensors") |
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``` |
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## Citation |
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If you use this model, please cite: |
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``` |
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@misc{nrm2025, |
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title={NRM: Nvyra Recursive Reasoning Model}, |
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author={Nvyra X Research Team}, |
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year={2025}, |
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url={https://huggingface.co/Feargal/nvyra-x-reasoning} |
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} |
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``` |
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## References |
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- [Universal Reasoning Model (URM)](https://arxiv.org/abs/2512.14693) |
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- [DeepSeek-V3](https://arxiv.org/abs/2401.02954) |
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- [PonderNet](https://arxiv.org/abs/2107.05407) |
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