| license: mit | |
| # BarcodeMamba for Taxonomic Classification | |
| A performant and efficient Mamba-2-based foundation model for DNA barcodes in biodiversity analysis. | |
| - Check out our [paper](https://openreview.net/forum?id=6ohFEFTr10) | |
| - Check out our [poster](https://neurips.cc/media/PosterPDFs/NeurIPS%202024/105938.png) | |
| # Usage | |
| The pretrained models can be used for both taxonomic classification on seen species (fine-tune & linear probe) and making genus-level predictions on unseen species (1-NN probe). The instructions for using our models can be found at our [GitHub repository](https://github.com/bioscan-ml/BarcodeMamba). | |
| # Citation | |
| If you find BarcodeMamba useful, please consider citing: | |
| ``` | |
| @inproceedings{ | |
| gao2024barcodemamba, | |
| title={BarcodeMamba: State Space Models for Biodiversity Analysis}, | |
| author={Tiancheng Gao and Graham W.~Taylor}, | |
| booktitle={{NeurIPS} 2024 Workshop on Foundation Models for Science: Progress, Opportunities, and Challenges}, | |
| year={2024}, |