jtreminio/swarmui repository overview

⁠swarm-container

This repo builds a SwarmUI⁠-ready container with:

• Nvidia PyTorch Container 26.01-py3⁠
  • python 3.12.3
  • cuda 13.1.1
  • torch 2.10.0
  • pytorch-triton 3.6.0
• sageattn3⁠
• sageattention 2.2.0⁠
• flash-attn 2.7.4⁠
• torchaudio 2.9.1⁠

It is built on top of the nvidia PyTorch images nvcr.io/nvidia/pytorch⁠.

⁠Requirements

• A Blackwell GPU
  • RTX 50-series
  • RTX Pro 6000
  • RTX Pro 5000
• Docker or Podman

⁠Getting Started

The image is available on DockerHub, so all you need to do is have the SwarmUI repo⁠ cloned locally. Replace /path/to/SwarmUI with the path you've cloned SwarmUI at locally and run one of the following:

⁠All model paths as default

docker run --gpus all -it -d --shm-size=8g --restart=always --name swarmui \
    -p 7801:7801 \
    -v /path/to/SwarmUI:/workspace \
    -v swarm_pip:/usr/local/lib/python3.12/dist-packages \
    jtreminio/swarmui:26.01-py3

Then navigate to http://localhost:7801/⁠.

⁠Define different model and config paths

docker run --gpus all -it -d --shm-size=8g --restart=always --name swarmui \
    -p 7801:7801 \
    -v /path/to/SwarmUI:/workspace \
    -v swarm_pip:/usr/local/lib/python3.12/dist-packages \
    -v /path/to/local/output_directory:/workspace/Output \
    -v /path/to/local/wildcard_directory:/workspace/Data/Wildcards \
    jtreminio/swarmui:26.01-py3

Then navigate to http://localhost:7801/⁠.

⁠More Tags

See all available tags at https://hub.docker.com/r/jtreminio/swarmui⁠.

⁠Building

If you would like to build the image for yourself, simply run:

# compiles sageattention, torchaudio, etc
./step-1.sh
# builds the Docker image for reuse
./step-2.sh

There are two steps because docker build does not have a --gpus all option, so you cannot compile anything that requires a GPU.