Update README.md

README.md

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-license: mit
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+# swarm-container
+
+This repo builds a [SwarmUI](https://github.com/mcmonkeyprojects/SwarmUI)-ready container with:
+
+* [flash_attn @ 2.7.4](https://github.com/Dao-AILab/flash-attention)
+* [sageattention @ 2.2.0](https://github.com/thu-ml/SageAttention)
+* [sageattn @ 3 (compiled)](https://github.com/thu-ml/SageAttention/tree/main/sageattention3_blackwell)
+* [torchaudio @ 2.9.1 (compiled)](https://github.com/pytorch/audio)
+
+It is built on top of the [nvidia PyTorch images nvcr.io/nvidia/pytorch](https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/index.html).
+
+# 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](https://github.com/mcmonkeyprojects/SwarmUI) 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
+
+```bash
+docker run --gpus all --rm -it --shm-size=512m --name swarmui \
+    -p 7801:7801 \
+    -v /path/to/SwarmUI:/workspace \
+    jtreminio/swarmui:latest
+```
+
+Then navigate to [http://localhost:7801/](http://localhost:7801/).
+
+## Define different model and config paths
+
+```bash
+docker run --gpus all --rm -it --shm-size=512m --name swarmui \
+    -p 7801:7801 \
+    -v /path/to/SwarmUI:/workspace \
+    -v /path/to/local/output_directory:/workspace/Output \
+    -v /path/to/local/wildcard_directory:/workspace/Data/Wildcards \
+    jtreminio/swarmui:latest
+```
+
+Then navigate to [http://localhost:7801/](http://localhost:7801/).
+
+# Building
+
+If you would like to build the image for yourself, simply run:
+
+```bash
+# compiles flash_attn, 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.