Metadata-Version: 2.1
Name: m2pt
Version: 0.0.1
Summary: M2PT - Pytorch
Home-page: https://github.com/kyegomez/M2PT
License: MIT
Keywords: artificial intelligence,deep learning,optimizers,Prompt Engineering
Author: Kye Gomez
Author-email: kye@apac.ai
Requires-Python: >=3.6,<4.0
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Dist: swarms
Requires-Dist: zetascale
Project-URL: Documentation, https://github.com/kyegomez/M2PT
Project-URL: Repository, https://github.com/kyegomez/M2PT
Description-Content-Type: text/markdown

[![Multi-Modality](agorabanner.png)](https://discord.gg/qUtxnK2NMf)

# Multi-Modal Pathway Transformer
Implementation of M2PT in PyTorch from the paper: "Multimodal Pathway: Improve Transformers with Irrelevant Data from Other Modalities".  [PAPER LINK](https://arxiv.org/abs/2401.14405)


## Install


## Citation
```bibtex
@misc{zhang2024multimodal,
    title={Multimodal Pathway: Improve Transformers with Irrelevant Data from Other Modalities}, 
    author={Yiyuan Zhang and Xiaohan Ding and Kaixiong Gong and Yixiao Ge and Ying Shan and Xiangyu Yue},
    year={2024},
    eprint={2401.14405},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}
```


# License
MIT

