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--- |
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tags: |
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- docker |
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- x86 |
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- a100 |
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- rtx4090 |
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- semamba |
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- cuda |
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- pytorch |
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- mamba |
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license: mit |
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library_name: docker |
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datasets: [] |
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--- |
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# x86 SEMamba Docker Image |
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This Docker image provides a pre-configured development environment for running [SEMamba](https://github.com/RoyChao19477/SEMamba) models on x86 systems such as NVIDIA A100, RTX 4090, and other CUDA-compatible GPUs. It contains Python 3.12 and PyTorch 2.2.2, built on top of Ubuntu 22.04 with CUDA 12.4. |
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## Contents |
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- **OS**: Ubuntu 22.04 (x86_64) |
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- **Python**: 3.12 (via Miniconda) |
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- **CUDA**: 12.4 (base image) |
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- **PyTorch**: 2.2.2 |
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- **TorchVision**: 0.17.2 |
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- **TorchAudio**: 2.2.2 |
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- **Mamba-SSM**: 1.2.0 |
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- **Essential packages**: git, vim, screen, htop, tmux, openssh, etc. |
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## Usage |
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### Download Docker Image |
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```bash |
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wget https://huggingface.co/datasets/rc19477/x86-semamba-docker/resolve/main/x86_semamba_py312_pt222_cuda124.tar |
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``` |
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### Load Docker Image |
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```bash |
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docker load < x86_semamba_py312_pt222_cuda124.tar |
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``` |
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### Run Container |
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```bash |
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docker run --gpus all -it -v $(pwd):/workspace x86_semamba_py312_pt222_cuda124 |
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``` |
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This will mount your current directory into `/workspace` inside the container. |
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## Purpose |
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- Simplifies setup for SEMamba on x86 GPU systems |
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- Provides reproducible environment with version-pinned core libraries |
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## License & Attribution |
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- This Docker image is shared for **non-commercial research purposes**. |
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- All included libraries retain their original licenses. |
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- Based on [PyTorch](https://pytorch.org/), [Miniconda](https://docs.conda.io/en/latest/miniconda.html), and [Mamba](https://github.com/state-spaces/mamba). |
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## Maintainer |
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For questions or issues, feel free to open a discussion or connect via GitHub. |
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