setup-cog

Cog is an open-source tool that lets you package machine learning models in a standard, production-ready container. To learn more about Cog, visit cog.run.

This repo is a GitHub Action that makes it easy to install Cog on a GitHub-hosted runner so you can run, test, and push machine learning models to Replicate, or to your own infrastructure. This action takes care of setting up prerequisites like Dockerx and NVIDIA's CUDA drivers, so you can focus on building and deploying your models without the headache.

⚡️ Cog supports building and pushing GPU models from machines that don't have GPUs ⚡️. So in many cases you can use this action to push your GPU model to Replicate, even if you're using a GitHub-hosted runner that doesn't have a GPU.

Usage

Add a step to your workflow that uses this action:

- name: Setup Cog
  uses: replicate/setup-cog@v2
  with:
    token: ${{ secrets.REPLICATE_API_TOKEN }}

- name: Download weights
  run: cog run script/download-weights

- name: Push to Replicate
  run: cog push r8.im/zeke/hello-world

Now you can run the cog CLI in subsequent steps to cog run, cog push, etc.

Inputs

This following inputs can be specified using the with keyword:

cog-version

The version of Cog to install in the form vX.Y.Z. See Cog releases for a list of available versions.

Defaults to v0.9.8.

- name: Setup Cog
  uses: replicate/setup-cog@v2
  with:
    cog-version: "v0.9.9-alpha"

token

Your Replicate API token. If set, the Action will automatically authenticate to Replicate using cog login. To use this feature, create a token at replicate.com/account/api-tokens, copy it, then paste it into a repository secret named REPLICATE_API_TOKEN in your GitHub repo's settings.

- name: Setup Cog
  uses: replicate/setup-cog@v2
  with:
    token: ${{ secrets.REPLICATE_API_TOKEN }}

install-cuda

Install NVIDIA CUDA Toolkit. Defaults to false, because most Cog models can be built and pushed without requiring CUDA. Cog supports building and pushing GPU models from machines that don't have GPUs, so in many cases you can push your GPU model to Replicate without installing the toolkit.

If you need CUDA installed, set this input to true:

- name: Setup Cog
  uses: replicate/setup-cog@v2
  with:
    install-cuda: true

Example: Manual Deployment

Here's an example that allows you to trigger a workflow run manually from the Actions tab in your repo:

name: Push to Replicate

on:
  workflow_dispatch:
    inputs:
      model_name:
        required: true
        description: "The name of the Replicate model to publish, e.g `username/modelname`. The model must already exist on Replicate."

jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - name: Check out code
        uses: actions/checkout@v3

      - name: Setup Cog
        uses: replicate/setup-cog@v2
        with:
          token: ${{ secrets.REPLICATE_API_TOKEN }}

      - name: Push to Replicate
        run: |
          cog push r8.im/${{ inputs.model_name }}

Example: Continuous Deployment

Here's an example that pushes to Replicate whenever your repo's main branch is updated:

name: Push to Replicate

on:
  push:
    branches:
      - main

jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - name: Check out code
        uses: actions/checkout@v3

      - name: Setup Cog
        uses: replicate/setup-cog@v2
        with:
          token: ${{ secrets.REPLICATE_API_TOKEN }}

      - name: Push to Replicate
        run: |
          cog push r8.im/zeke/hello-world

Limitations

GitHub's hosted runners don't have GPUs (yet?), so you can't currently run GPU models unless you self-host your own runner.

That said, Cog can still be used to build and push GPU models, even from a Linux environment that doesn't have a GPU. So you can push GPU models to Replicate, but you can't run them as part of your workflow.

Using custom hosted runners

This action works on GitHub's default runners, but most models require more disk space and memory than is available on the default runner.

GitHub offers more powerful hosted runners that are easy to set up with just a few clicks, but you'll have to Sign up for GitHub's Hosted Runners beta before you can use them. Note that these runners are only available on paid Team or Enterprise plans, so you'll need to make sure your model repository is owned by a paid GitHub organization rather than an individual user account.

Once you've set up a hosted runner, you can use it by adding the runs-on key to your job:

jobs:
  do_cog_stuff:
    runs-on: my-fancy-runner-with-more-disk-and-memory
    steps:
      - name: Check out code
        uses: actions/checkout@v3

      - name: Setup Cog
        uses: replicate/setup-cog@v2