Migrating Your GitHub CI to Hugging Face Jobs

If you have a GitHub repository and you have GitHub Actions enabled, you probably use GitHub-hosted runners for CI. That is the default for many projects because it is simple: add a workflow, write runs-on: ubuntu-latest , and GitHub gives you a machine.

That default is convenient, but it also has limits. GitHub Actions can be slow or down for maintenance, the hosted machines are generic, and GPU access is not something most open-source projects can just turn on. For Trackio , those limits started to matter. We wanted both reliable CPU CI for basic unit tests and frontend checks, but also GPU CI for tests that need to run on actual CUDA hardware.

So built an alternative: keep GitHub Actions in charge of CI, but run the jobs on Hugging Face Jobs .

From GitHub's point of view, this is just a self-hosted runner. From Hugging Face's point of view, it is just a Job that launches a container to run the workflow steps from the repo’s GitHub Actions.

Use cpu-upgrade for real CI so the dispatcher stays available for GitHub webhooks. cpu-basic is fine for testing and will probably work, but it can sleep after inactivity; if GitHub's webhook arrives while it is waking up, the workflow may stay queued forever.

If you'd prefer to set up the dispatcher Space with an agent or use a CLI workflow:

The result: Trackio's CI now runs on Hugging Face Jobs and streams back real-time logs, cutting our CI time for CPU jobs by about 30% and enabling a whole new test suite that runs on GPU machines !

In this article, we explain step-by-step how to recreate the same setup for your GitHub repo. If you are using an agent, you can point it to this article, since we provide CLI instructions alongside browser-based instructions for us humans.

Hugging Face Jobs lets you run commands or scripts on Hugging Face's serverless infrastructure with almost any hardware flavor. A Job is essentially: