Upload folder using huggingface_hub

README.md

@@ -0,0 +1,72 @@
+---
+tags:
+  - docker
+  - x86
+  - a100
+  - rtx4090
+  - semamba
+  - cuda
+  - pytorch
+  - mamba
+license: mit
+library_name: docker
+datasets: []
+---
+
+# x86 SEMamba Docker Image
+
+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 is optimized for Python 3.12 and PyTorch 2.2.2, built on top of Ubuntu 22.04 with CUDA 12.4.
+
+---
+
+## Contents
+
+- **OS**: Ubuntu 22.04 (x86_64)
+- **Python**: 3.12 (via Miniconda)
+- **CUDA**: 12.4 (base image)
+- **PyTorch**: 2.2.2
+- **TorchVision**: 0.17.2
+- **TorchAudio**: 2.2.2
+- **Mamba-SSM**: 1.2.0
+- **Essential packages**: git, vim, screen, htop, tmux, openssh, etc.
+
+---
+
+## Usage
+
+### Load Docker Image
+
+```bash
+docker load < x86_semamba_py312_pt222_cuda124.tar
+```
+
+### Run Container
+
+```bash
+docker run --gpus all -it -v $(pwd):/workspace x86_semamba_py312_pt222_cuda124
+```
+
+This will mount your current directory into `/workspace` inside the container.
+
+---
+
+## Purpose
+
+- Simplifies setup for high-performance x86 GPU systems
+- Ideal for SEMamba experiments using FlashAttention and custom CUDA builds
+- Provides reproducible environment with version-pinned core libraries
+
+---
+
+## License & Attribution
+
+- This Docker image is shared for **non-commercial research purposes**.
+- All included libraries retain their original licenses.
+- Based on [PyTorch](https://pytorch.org/), [Miniconda](https://docs.conda.io/en/latest/miniconda.html), and [Mamba](https://github.com/state-spaces/mamba).
+
+---
+
+## Maintainer
+
+For questions or issues, feel free to open a discussion or connect via GitHub.
+