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DeepSeek-R1-TrRa-1.5B-lambda_2
wh-zhu/DeepSeek-R1-TrRa-1.5B-lambda_2
DeepSeek-R1-TrRa-1.5B-lambda_2 is a machine learning model from wh-zhu. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
<h1 align="center"🛠️ ReAligner</h1 <p align="center" <a href="https://arxiv.org/pdf/2506.12704"<img src="https://img.shields.io/badge/arXiv-arXiv%20Preprint-B31B1B?style=flat&logo=arxiv&logoColor=white" alt="arXiv Pa…
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At a glance
- Model type
- qwen2
- Access
- Public
- Created
- May 28, 2025
- Updated
- Jun 17, 2025
- SHA
- b3f11565
Model card
From the Hugging Face model README
<h1 align="center">🛠️ ReAligner</h1>
<p align="center">
<a href="https://arxiv.org/pdf/2506.12704"><img src="https://img.shields.io/badge/arXiv-arXiv%20Preprint-B31B1B?style=flat&logo=arxiv&logoColor=white" alt="arXiv Paper"></a>
<a href="https://github.com/zwhong714/ReAligner"><img src="https://img.shields.io/badge/Homepage-Project%20Page-brightgreen?style=flat&logo=github" alt="Homepage"></a>
<a href="https://huggingface.co/wh-zhu"><img src="https://img.shields.io/badge/Huggingface-Models-yellow?style=flat&logo=huggingface" alt="Models"></a>
</p>
<div>
A flexible realignment framework is proposed to quantitatively control alignment during training and inference, combining Training-time Realignment (TrRa) and Inference-time Realignment (InRa).
- We realign DeepScaleR-1.5B model and reduce token usage without performance loss and even enhance reasoning capabilities.
- Type
- qwen2
- Created
- May 28, 2025
- Updated
- Jun 17, 2025