v0.7.12

Native install (Apple Silicon / homelab)

uv tool install "mship[metal]"
mship deploy --config models.yaml

Docker images

Thin (control/coordinator — default, no torch/vllm)

docker pull ghcr.io/modelship-ai/modelship:0.7.12

CUDA (GPU node)

docker pull ghcr.io/modelship-ai/modelship:0.7.12-cuda

CPU (CPU node)

docker pull ghcr.io/modelship-ai/modelship:0.7.12-cpu

Floating tags (:latest, :latest-cuda, :latest-cpu) are single-node only — for any
multi-node cluster, pin every node to the same X.Y.Z tag to avoid a Ray version
mismatch between head and workers.

Helm chart (Kubernetes)

helm install modelship \
  oci://ghcr.io/modelship-ai/charts/modelship \
  --version 0.7.12 \
  -f values.yaml

Configuration

Create a models.yaml file and mount it at /modelship/config/models.yaml. Example configs for various GPU sizes are included in the image under /modelship/config/ — use them as a reference for structure and available options, then tailor the models and GPU fractions to your hardware.

What's Changed

• Feat/mship cpu native install by @alez007 in #168
• ci: add Linux CUDA llama.cpp backend build workflow by @alez007 in #169
• Ci/llama cpp cuda publish guard by @alez007 in #170
• Ci/llama cpp unified build by @alez007 in #171
• Feat/native cuda install by @alez007 in #172
• Feat/bootstrapper by @alez007 in #173

Full Changelog: v0.7.11...v0.7.12