README.md

---
library_name: transformers
license: mit
---

# Model Card for GERM

<!-- Provide a quick summary of what the model is/does. -->



## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

- **Developed by:** Haozheng Luo, ChengHao Qiu
- **License:** MIT

### Model Sources

<!-- Provide the basic links for the model. -->

- **Repository:** https://github.com/MAGICS-LAB/GERM
- **Paper:** https://arxiv.org/abs/2505.00598

## Uses

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->

### Direct Use

```
from transformers import AutoTokenizer, AutoModelForMaskedLM

tokenizer = AutoTokenizer.from_pretrained("magicslabnu/GERM", trust_remote_code=True)
model = AutoModelForMaskedLM.from_pretrained("magicslabnu/GERM", trust_remote_code=True)
```

## Training Details

### Training Data

<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->

GLUE



**BibTeX:**
```
@misc{luo2025fastlowcostgenomicfoundation,
      title={Fast and Low-Cost Genomic Foundation Models via Outlier Removal}, 
      author={Haozheng Luo and Chenghao Qiu and Maojiang Su and Zhihan Zhou and Zoe Mehta and Guo Ye and Jerry Yao-Chieh Hu and Han Liu},
      year={2025},
      eprint={2505.00598},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2505.00598}, 
}
```