Paper - Pytorch
Project description
MoE Mamba
Implementation of MoE Mamba from the paper: "MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts" in Pytorch and Zeta.
Install
pip install moe-mamba
Usage
print("hello world")
Code Quality 🧹
make style
to format the codemake check_code_quality
to check code quality (PEP8 basically)black .
ruff . --fix
Citation
@misc{pióro2024moemamba,
title={MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts},
author={Maciej Pióro and Kamil Ciebiera and Krystian Król and Jan Ludziejewski and Sebastian Jaszczur},
year={2024},
eprint={2401.04081},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
License
MIT
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
moe_mamba-0.0.1.tar.gz
(2.9 kB
view hashes)
Built Distribution
Close
Hashes for moe_mamba-0.0.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | bd4f22102ad34fcca2ce7e0b1c754a8a1f4941af1e60982e401884692ac18567 |
|
MD5 | c87b4eae67c322cc1f79817d0add9614 |
|
BLAKE2b-256 | 214b7d739201528a206a47a568e49aaddc6578945c717b929c908847bb3c930b |