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--- |
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datasets: |
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- liuhaotian/LLaVA-Pretrain |
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pipeline_tag: image-text-to-text |
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library_name: transformers.js |
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license: apache-2.0 |
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language: |
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- en |
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metrics: |
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- accuracy |
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--- |
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<p align="center"> |
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<img src="https://i.imgur.com/BVjGIik.png" alt="Hyze Logo" width="100"/> |
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<img src="https://i.imgur.com/ePJMLNp.png" alt="Founder" width="405"/> |
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</p> |
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<h1 align="center">Hyze RE1 Pro</h1> |
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<p align="center"> |
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20B Open-Weight Research Model by <b>Hyze AI</b> |
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</p> |
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<p align="center"> |
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π <a href="https://hyzeai.vercel.app">hyzeai.vercel.app</a> β’ |
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π <a href="https://hyzedocs.vercel.app">hyzedocs.vercel.app</a> β’ |
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π§ <a href="https://hyzecode.vercel.app">hyzecode.vercel.app</a> |
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</p> |
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--- |
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## π Overview |
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**Hyze RE1 Pro** is a **20-billion parameter transformer model** designed exclusively for **research and advanced reasoning tasks**. |
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Built on the philosophy that: |
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> Frontier AI should not belong only to billion-dollar budgets. |
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RE1 Pro delivers strong reasoning performance in a **fully open-weight package**, empowering researchers, developers, and independent innovators. |
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--- |
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## π§ Core Focus |
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Hyze RE1 Pro is optimized for: |
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- π¬ Advanced reasoning |
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- π Research-oriented analysis |
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- π§© Multi-step problem solving |
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- π Long-form structured explanations |
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- π§ Logical and technical tasks |
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This model prioritizes **clarity, depth, and reasoning structure** over casual chat behavior. |
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--- |
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## π Model Specifications |
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- **Architecture:** Transformer |
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- **Parameters:** 20 Billion |
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- **Type:** Open-weight research model |
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- **Primary Domain:** Reasoning & Research |
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- **Language:** English |
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--- |
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## π§ͺ Intended Use |
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Hyze RE1 Pro is designed for: |
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- Academic research experiments |
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- Independent AI research labs |
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- Reasoning benchmark testing |
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- Long-form technical analysis |
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- Open-weight innovation |
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--- |
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## β‘ Why RE1 Pro? |
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While many frontier models remain closed and restricted, RE1 Pro embraces: |
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- β
Accessibility |
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- β
Transparency |
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- β
Open experimentation |
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- β
Independent research freedom |
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It aims to reduce the barrier between individual researchers and high-performance AI systems. |
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--- |
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## β οΈ Limitations |
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- Large compute requirements (20B parameters) |
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- Not optimized for casual short-form chat |
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- Outputs should be validated in academic or production contexts |
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--- |
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## π§ͺ Example Usage |
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```python |
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from transformers import pipeline |
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generator = pipeline( |
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"text-generation", |
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model="HyzeAI/Hyze-RE1-Pro" |
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) |
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print(generator("Explain the mathematical intuition behind backpropagation.")) |