publish-models

---name: publish-modelsdescription: >---

Docs

• Cog reference: https://cog.run/llms.txt
• cog push reference: https://cog.run/cli#cog-push
• cog-safe-push: https://github.com/replicate/cog-safe-push
• Model CI template: https://github.com/replicate/model-ci-template
• Continuous deployment guide: https://replicate.com/docs/guides/continuous-model-deployment

When to use this skill

• You have a working Cog project (see build-models if you don't yet).
• You want to publish a private or public model on Replicate.
• You're releasing a new version of an existing model and want to avoid breaking changes.
• You're setting up CI/CD for model releases.

Prerequisites

• Cog installed and cog login against r8.im (or echo $TOKEN | cog login --token-stdin).
• A model created at replicate.com/{owner}/{name} via the API, web UI, or r8-model CLI.
• REPLICATE_API_TOKEN set in your environment.

Plain cog push

The simplest path. Build and upload a new version:

cog push r8.im/owner/my-model

Or set image: r8.im/owner/my-model in cog.yaml and run a bare:

cog push

Useful flags:

• --separate-weights — store weights in a separate layer; faster cold boots and pushes for models with > 1GB of weights.
• --x-fast — faster pushes during iteration (skips some validation).
• --secret id=hf,src=$HOME/.hf_token — pass build-time secrets without baking them into image history.

cog-safe-push (recommended for any model with users)

cog-safe-push pushes to a private -test model first, checks schema compatibility against the live version, runs prediction comparisons, and fuzzes inputs. Catches breaking changes before they reach users.

Install:

pip install git+https://github.com/replicate/cog-safe-push.git

Required env vars:

• REPLICATE_API_TOKEN
• ANTHROPIC_API_KEY (Claude judges output similarity for stochastic models)

Basic usage:

cog-safe-push --test-hardware=gpu-l40s owner/my-model

This will:

1. Lint predict.py with ruff.
2. Create a private test model owner/my-model-test if missing.
3. Push the local Cog model to the test model.
4. Lint the schema (descriptions, defaults, etc.).
5. Check schema compatibility against the live owner/my-model version.
6. Run prediction comparisons between live and test versions.
7. Fuzz the test model with AI-generated inputs.
8. If everything passes, push to owner/my-model.

cog-safe-push.yaml schema

Drop a cog-safe-push.yaml in your project root (or cog-safe-push-configs/<variant>.yaml for multi-model repos). All five test-case checker types in one example:

model: owner/my-model
test_model: owner/my-model-test
test_hardware: gpu-l40s

predict:
  compare_outputs: false              # set false for stochastic models
  predict_timeout: 600
  test_cases:
    - inputs:
        prompt: "a serene mountain landscape"
      match_prompt: "a landscape photo of mountains"   # AI-judged via Claude
    - inputs:
        prompt: "a cat"
      match_url: "https://example.com/reference-cat.png"   # binary/image match
    - inputs:
        prompt: ""
      error_contains: "prompt cannot be empty"           # negative test
    - inputs:
        mode: "json"
      jq_query: '.confidence > 0.8 and .status == "success"'   # JSON output
    - inputs:
        prompt: "echo this"
      exact_string: "echo this"                          # exact string match
  fuzz:
    fixed_inputs:
      seed: 42
    disabled_inputs:
      - debug
    iterations: 10
    prompt: "Generate creative and diverse prompts"

train:                                  # if your model has a trainer
  destination: owner/my-model-trained
  destination_hardware: gpu-l40s
  train_timeout: 1800
  test_cases:
    - inputs:
        input_images: "https://.../training.zip"
        steps: 10

deployment:                             # auto-create or update on push
  name: my-model
  owner: owner
  hardware: gpu-l40s

parallel: 4
fast_push: false
ignore_schema_compatibility: false
official_model: owner/my-model         # for proxy/wrapper models, see below

Test case checkers are mutually exclusive: pick exactly one of match_prompt, match_url, error_contains, jq_query, or exact_string per case. Use compare_outputs: false for any stochastic model (diffusion, LLMs); the default true is brittle.

CI/CD: GitHub Actions

Two paths, depending on how much glue you want.

Path A: roll your own

# .github/workflows/push.yaml
name: Push to Replicate
on:
  workflow_dispatch:
    inputs:
      no_push:
        type: boolean
        default: false

jobs:
  push:
    runs-on: ubuntu-latest-4-cores       # builds need disk + cores
    steps:
      - uses: actions/checkout@v4
      - uses: jlumbroso/free-disk-space@v1.3.1
        with:
          tool-cache: false
          docker-images: false
      - uses: replicate/setup-cog@v2
        with:
          token: ${{ secrets.REPLICATE_API_TOKEN }}
      - run: pip install git+https://github.com/replicate/cog-safe-push.git
      - env:
          ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
          REPLICATE_API_TOKEN: ${{ secrets.REPLICATE_API_TOKEN }}
        run: |
          cog-safe-push -vv ${{ inputs.no_push && '--no-push' || '' }}

Add a concurrency: block so PR builds cancel each other while main-branch pushes queue:

concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: ${{ github.ref != 'refs/heads/main' }}

Path B: reusable workflow from model-ci-template

For Replicate-style multi-model repos, drop in:

# .github/workflows/ci.yaml
name: CI
on:
  pull_request: { branches: [main] }
  push: { branches: [main] }
  workflow_dispatch:
    inputs:
      models: { type: string, default: "all" }
      ignore_schema_checks: { type: boolean, default: false }
      cog_version: { type: string, default: "latest" }
      test_only: { type: boolean, default: false }

jobs:
  ci:
    uses: replicate/model-ci-template/.github/workflows/template.yaml@main
    with:
      trigger_type: ${{ github.event_name }}
      models: ${{ inputs.models || 'all' }}
      ignore_schema_checks: ${{ inputs.ignore_schema_checks || false }}
      cog_version: ${{ inputs.cog_version || 'latest' }}
      test_only: ${{ inputs.test_only || false }}
    secrets: inherit

The reusable workflow expects:

• cog-safe-push-configs/<model>.yaml — one per model variant.
• script/select-model — bash file with if/elif [[ "$MODEL" == "..." ]] blocks listing valid model names.
• Secrets: COG_TOKEN, REPLICATE_API_TOKEN, ANTHROPIC_API_KEY.

Multi-model matrix pushes

Pattern from replicate/cog-flux: one repo, N variants, push them in parallel.

jobs:
  prepare:
    runs-on: ubuntu-latest
    outputs:
      matrix: ${{ steps.set.outputs.matrix }}
    steps:
      - id: set
        run: |
          if [ "${{ inputs.models }}" = "all" ]; then
            echo 'matrix={"model":["schnell","dev","krea-dev"]}' >> "$GITHUB_OUTPUT"
          else
            list=$(echo "${{ inputs.models }}" | jq -Rc 'split(",")')
            echo "matrix={\"model\":$list}" >> "$GITHUB_OUTPUT"
          fi

  push:
    needs: prepare
    runs-on: ubuntu-latest-4-cores
    strategy:
      fail-fast: false
      matrix: ${{ fromJson(needs.prepare.outputs.matrix) }}
    steps:
      - uses: actions/checkout@v4
      - run: ./script/select.sh ${{ matrix.model }}     # produces cog.yaml from a template
      - run: cog-safe-push --config cog-safe-push-configs/${{ matrix.model }}.yaml -vv

Two-pass push for proxy / official models

When you maintain a proxy that wraps a third-party API, you push to a private wrapper first, then update the public-facing official model card. Pattern from replicate/cog-official-template:

./script/write-api-key                                              # bake API key into config
cog-safe-push --config cog-safe-push-configs/${MODEL}.yaml -vv

./script/delete-api-key                                             # strip the key
cog-safe-push --push-official-model --config cog-safe-push-configs/${MODEL}.yaml -vv

Set official_model: owner/name in the config so --push-official-model knows where to publish.

Deployments

Add a deployment block to cog-safe-push.yaml to create or update a Replicate deployment automatically on each push:

deployment:
  name: my-model
  owner: owner
  hardware: gpu-l40s

Scaling defaults: CPU deployments scale 1-20 instances, GPU deployments scale 0-2. Adjust manually via the API or web UI when needed.

Monitoring published models

Run an hourly canary that exercises the registry path. Pattern from replicate/cog-pagerduty-check:

name: Hourly cog push check
on:
  schedule:
    - cron: "0 * * * *"
  workflow_dispatch:

jobs:
  check:
    runs-on: ubuntu-latest
    steps:
      - run: |
          # generate a tiny model with a unique uuid, push it, run a prediction
          # by digest, fail loudly if anything breaks.
          ./script/canary.sh

Worth doing for any production-critical model, especially when revenue depends on the registry being up.

Guidelines

• Don't break schema compatibility unless you mean to. cog-safe-push catches it; --ignore-schema-compatibility is the opt-out.
• Pin test_hardware so test pushes are reproducible.
• Use --no-push for dry runs in PR CI; full push on merge to main or on version tags.
• Push from CI rather than laptops once you have users.
• Use compare_outputs: false for stochastic models. Use match_prompt: for image/video outputs (VLM judgment), match_url: for binary outputs you control, jq_query: for JSON, error_contains: for negative tests.
• Never commit REPLICATE_API_TOKEN or ANTHROPIC_API_KEY. Use repo secrets.
• For models with weights > 1GB, push with --separate-weights.

Production references

• https://github.com/replicate/cog-safe-push — the tool itself, plus its config schema.
• https://github.com/replicate/model-ci-template — reusable GitHub Actions workflow.
• https://github.com/replicate/cog-official-template — proxy/official model template.
• https://github.com/replicate/cog-flux/blob/main/.github/workflows/push.yaml — matrix push across FLUX variants.
• https://github.com/replicate/cog-comfyui/blob/main/.github/workflows/ci.yaml — ComfyUI model CI with custom-node install step.
• https://github.com/replicate/cog-pagerduty-check — hourly canary pattern.