Audio xLSTMs: Learning Self-supervised audio representations with xLSTMs
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
@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}
}
Metadata
Release files for audio-xlstm 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| audio_xlstm-0.0.1.tar.gz | 8.6 kB | Without provenance | Details for audio_xlstm-0.0.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| audio_xlstm-0.0.1-py3-none-any.whl | Python 3 | none | any | Details for audio_xlstm-0.0.1-py3-none-any.whl |
Total release size: 17.5 kB
Release files / audio_xlstm-0.0.1.tar.gz
| Download URL | audio_xlstm-0.0.1.tar.gz |
|---|---|
| Size | 8.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
ddf174cce127f3a921978a49f7ada318f47d86c8b08aeebe01604a4748686eec
|
|
BLAKE2b-256 checksum How to use checksums |
9845ee74bfdc3ee282feae4f345fb893d8db66dadaac5e3f730a23e40517a93f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.8.3 CPython/3.12.3 Darwin/23.3.0
|
Release files / audio_xlstm-0.0.1-py3-none-any.whl
| Download URL | audio_xlstm-0.0.1-py3-none-any.whl |
|---|---|
| Size | 8.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
db795ea07df6216eb7dc85852dd3ed57985b6a011b0e9dd52987ae0ef29a6fff
|
|
BLAKE2b-256 checksum How to use checksums |
59ceb690e0b28a1fc3d8ae3a24110b97064542fad6344705afbe7b1cc5c23eb0
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.8.3 CPython/3.12.3 Darwin/23.3.0
|
Security for audio-xlstm 0.0.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.