Metadata-Version: 2.1
Name: audio-xlstm
Version: 0.0.1
Summary: Paper - Pytorch
Home-page: https://github.com/kyegomez/Audio-xLSTMs
License: MIT
Keywords: artificial intelligence,deep learning,optimizers,Prompt Engineering
Author: Kye Gomez
Author-email: kye@apac.ai
Requires-Python: >=3.10,<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 :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Dist: einops
Requires-Dist: tokenizers
Requires-Dist: torch
Requires-Dist: transformers
Project-URL: Documentation, https://github.com/kyegomez/Audio-xLSTMs
Project-URL: Repository, https://github.com/kyegomez/Audio-xLSTMs
Description-Content-Type: text/markdown

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# Audio xLSTMs: Learning Self-supervised audio representations with xLSTMs

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This is a community based approach to an implementation mostly for practice. I will implement the model architecture as defined in the paper but will leave someone else to implement the training script! So please create a training script if you have the time and energy




# License
MIT


# Citation
```bibtex
@article{xlstm,
  title={xLSTM: Extended Long Short-Term Memory},
  author={Beck, Maximilian and P{\"o}ppel, Korbinian and Spanring, Markus and Auer, Andreas and Prudnikova, Oleksandra and Kopp, Michael and Klambauer, G{\"u}nter and Brandstetter, Johannes and Hochreiter, Sepp},
  journal={arXiv preprint arXiv:2405.04517},
  year={2024}
}

```
