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ModelCache Custom Resource

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This document is for an older version of Modelplane.

This document applies to Modelplane v0.1 and not to the latest release v0.3.

Stage model weights on cluster storage before serving.

Concept guide: Cache Model Weights →

#Metadata

API version
modelplane.ai/v1alpha1
Kind
ModelCache
Scope
Namespaced
Short names
mc

#Example

Manifest
apiVersion: modelplane.ai/v1alpha1
kind: ModelCache
metadata:
  name: qwen-72b
  namespace: ml-team
spec:
  source: HuggingFace
  huggingFace:
    repo: Qwen/Qwen2.5-72B-Instruct
    sizeGiB: 150
    authSecret:
      name: hf-token
      key: HF_TOKEN

#Spec

# clusterSelector optional object

Label selector to pick the InferenceClusters that stage this artifact. If omitted, the cache replicates to every cluster.

# matchLabels optional map[string]string
# huggingFace optional object

HuggingFace source. Required when source is HuggingFace.

# authSecret optional object

Optional Secret holding an HF token for gated or private repos. Names a Secret in the ModelCache’s own namespace; Modelplane propagates it to each matched cluster for the hydration Job to read.

# key optional string default: HF_TOKEN
# name required string ≥ 1 chars
# repo required string ≥ 1 chars

HuggingFace repository ID.

# revision optional string

Branch, tag, or commit SHA. Defaults to the repo’s default branch.

# sizeGiB required integer 1–100000

Capacity to allocate for the staged artifact on each matched cluster.

# source required enum: HuggingFace

Which kind of artifact source to stage from. The matching source object (e.g. spec.huggingFace) must be set.

#Status

# clusters optional object[]
# message optional string
# name required string
# phase optional enum: Pending | Hydrating | Ready | Failed
# conditions optional object[]
# summary optional object

Per-cluster ready / total counts.

# ready optional string

e.g. “2/3”