GH200 SEMamba Docker Image

This Docker image provides a pre-configured development environment for running SEMamba, a mamba-based speech enhancement model, on NVIDIA GH200 hardware. It was created to save time and ensure reproducibility for ARM64/aarch64 CUDA 12.8 setups.

The image includes all required dependencies and configurations for Mamba-based speech enhancement research and other sequence modeling tasks.

⚠️ Warning on Package Source

This Docker image installs PyTorch, Mamba-SSM, triton, decord, vllm, and FlashAttention from the Jetson SBSA CUDA 12.8 index, which is a custom external package repository.

While it enables compatibility with ARM64 + CUDA 12.8 setups, users should be aware that:

It is not an official PyPI source

Packages may have undocumented patches or modifications

There may be potential security or reproducibility risks

Use with discretion, especially in sensitive or production-level environments.

OS: Ubuntu 24.04 (ARM64)
Python: 3.12
CUDA: 12.8
PyTorch: 2.7 (This package is installed from Jetson SBSA CUDA 12.8 index)
Mamba-SSM: v2.2.4 (This package is installed from Jetson SBSA CUDA 12.8 index)
FlashAttention: v2.7.4.post1 (This package is installed from Jetson SBSA CUDA 12.8 index)
Essential packages: ffmpeg, vim, htop, tmux, screen, etc.

Usage

Download Docker Image

wget https://huggingface.co/datasets/rc19477/gh200-semamba-docker/resolve/main/gh200_semamba_py312_pt27_cuda128.tar

Load Docker Image

docker load < gh200_semamba_py312_pt27_cuda128.tar

Run Container

docker run --gpus all -it -v $(pwd):/workspace gh200_semamba_py312_pt27_cuda128

This will mount your current directory into /workspace inside the container.

Notes

This image is intended only for GH200 (ARM64) systems with CUDA 12.8.
Python packages are installed via a custom PyPI index for ARM64 provided by Jetson AI Lab.
Do not use this image on x86 systems; it will not work.
This environment was built to support projects like SEMamba that use selective state space models.

License & Attribution

This Docker image is shared for non-commercial research purposes.
All third-party packages, including PyTorch, FlashAttention, and Mamba-SSM, retain their original licenses.
PyTorch was installed from a community-provided index: https://pypi.jetson-ai-lab.dev
Users are responsible for complying with the licenses of any included or downloaded components.

Acknowledgments

Thanks to the developers of:

Jetson AI Lab for maintaining ARM64-compatible PyTorch wheels.

Maintainer

For any issues, feel free to open a discussion or contact me.

Datasets:

rc19477
/

gh200-semamba-docker