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hidden-tiger-paper
hayulalab/hidden-tiger-paper
hidden-tiger-paper is a machine learning model from hayulalab. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
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Updated Jul 8, 2026
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At a glance
- License
- mit
- Access
- Public
- Created
- Jul 8, 2026
- Updated
- Jul 8, 2026
- SHA
- d07f847c
Model card
From the Hugging Face model README
Run inference — Hayula Research
Hayula AI Lab
Abstract
DeepSeek V3 and R1 represent the frontier of Mixture-of-Experts language models at 671 billion total parameters (37B active per token). Current hardware limitations restrict deployment to multi-GPU clusters: no single H100 (80GB), A100 (80GB), or consumer GPU can load the model at any practical quantization level. We demonstrate that the Apple M2 Ultra with 192GB unified memory is the only consumer-grade hardware capable of running this architecture, at IQ1_M quantization (139GB) fitting entirel
Files
| File | Description |
|---|---|
paper.md | Full paper (Markdown) |
README.md | This model card |
Citation
@techreport{hayulalab2026hiddentiger,
title={Run inference — Hayula Research},
author={Hayula AI Lab},
year={2026},
url={https://huggingface.co/hayulalab/hidden-tiger-paper}
}
hayulalab — Open Source AI Research
- License
- mit
- Created
- Jul 8, 2026
- Updated
- Jul 8, 2026