v0.7.11

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:0.7.11

CUDA (GPU node)

docker pull ghcr.io/modelship-ai/modelship:0.7.11-cuda

CPU (CPU node)

docker pull ghcr.io/modelship-ai/modelship:0.7.11-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 0.7.11 \
  -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

• fix: drop CoreML support from sherpa_onnx loader, CPU only by @alez007 in #165
• Fix/throttle download progress logs by @alez007 in #166
• fix: stop whispercpp loader's native/download logs bleeding into console by @alez007 in #167

Full Changelog: v0.7.10...v0.7.11