Migrating Your GitHub CI to Hugging Face Jobs

jobs-actions Dispatcher

Run GitHub Actions on Hugging Face Jobs

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.

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.

Let's start with a quick intro to Hugging Face Jobs!

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

t4-small

or h200

GPUFor example, you can run:

hf jobs run python:3.12 python -c "print('Hello world')"

or

hf jobs uv run --flavor a10g-small "https://raw.githubusercontent.com/huggingface/trl/main/trl/scripts/sft.py"

That makes Jobs a natural fit for CI. CI jobs are already command-driven, already run in clean environments, and often benefit from choosing exactly the right hardware. For ML libraries, the GPU case is especially compelling: you can run a test suite on real GPU hardware without maintaining your own always-on runner.

The key step is connecting GitHub Actions to HF Jobs, which we describe below.

For this setup, we created huggingface/jobs-actions

, a small bridge that turns a GitHub Actions job into an ephemeral self-hosted runner running inside an HF Job.

The complete flow looks like this:

runs-on

label is not available, for example hf-jobs-cpu-upgrade

or hf-jobs-t4-small

, and sends a signed workflow_job.queued

webhook to the dispatcher through the GitHub App.hf-jobs-*

label, mints a short-lived GitHub runner registration token, and starts an HF Job on the matching hardware.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.

The first thing you need is the dispatcher. This is a small Docker Space that receives GitHub workflow_job

webhook events and launches HF Jobs in response.

Create this first because the GitHub App needs a webhook URL, and that URL comes from the Space. This Space should be under your own namespace or under a Hugging Face org that you have write access to.

Go to huggingface/jobs-actions-dispatcher

and click Duplicate this Space.

Use:

Owner: your HF user or org
Name: jobs-actions-dispatcher
Hardware: cpu-upgrade

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.

After it builds, open the duplicated Space. You will see a section that says "Required Space secrets," which you can ignore for now. The landing page should display the GitHub App webhook URL you need in the next step. It will look like this:

https://YOUR-HF-NAMESPACE-jobs-actions-dispatcher.hf.space/webhook

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

export HF_NAMESPACE=your-hf-user-or-org
export SPACE_ID="$HF_NAMESPACE/jobs-actions-dispatcher"
hf repo duplicate huggingface/jobs-actions-dispatcher "$SPACE_ID" \
--type space \
--flavor cpu-upgrade \
--exist-ok

Then set:

export DISPATCHER_URL="https://${HF_NAMESPACE}-jobs-actions-dispatcher.hf.space"

Next, create and install the GitHub App from the dispatcher Space itself. This App needs permission to listen for queued workflow jobs and create ephemeral self-hosted runner registration tokens.

Open your duplicated dispatcher Space:

https://YOUR-HF-NAMESPACE-jobs-actions-dispatcher.hf.space

In the setup form, enter the GitHub repo whose CI should run on HF Jobs:

YOUR-GITHUB-ORG/YOUR-REPO

Then click the button to create the GitHub App. GitHub will ask you to choose a name for the App; the name can be anything, as long as it is available in your GitHub account or org. After you submit, the final screen tells you exactly how to upload the App credentials to the dispatcher Space with the hf

CLI.

Important note: you will need to provide an Hugging Face token that has permissions to launch Jobs, corresponding to your personal account or an org under which Jobs should be charged. This token should be saved as the HF_TOKEN

secret in your dispatcher Space.

Finally, you will install the App on the same GitHub repo you entered in the Space. In the Trackio setup, we installed it on gradio-app/trackio

.

The GitHub App manifest flow is still browser-based, but an agent can follow the same Space-driven path:

export HF_NAMESPACE=your-hf-user-or-org
export GITHUB_REPO=YOUR-GITHUB-ORG/YOUR-REPO
open "https://${HF_NAMESPACE}-jobs-actions-dispatcher.hf.space"

Paste $GITHUB_REPO

into the Space, click the GitHub App creation button, choose any available App name, and follow the generated GitHub instructions.

After the App exists, install it on your repo from the App settings page. For a GitHub org, the installation settings are under:

https://github.com/organizations/YOUR-GITHUB-ORG/settings/installations

At this point, the dispatcher Space should be configured. The GitHub App setup flow generated the commands that upload the App credentials, webhook secret, and Hugging Face token to the Space.

By default, HF Jobs are launched under the same namespace as the dispatcher Space. Optionally, set HF_NAMESPACE

as a Space variable if you want to bill jobs to a different Hugging Face user or org:

export SPACE_ID=YOUR-HF-NAMESPACE/jobs-actions-dispatcher
hf spaces variables add "$SPACE_ID" -e HF_NAMESPACE=your-billing-namespace
hf spaces restart "$SPACE_ID"

The token you set in Step 2 should correspond to this namespace.

The actual workflow change is small. Instead of:

runs-on: ubuntu-latest

use one of the labels handled by the dispatcher:

runs-on: hf-jobs-cpu-upgrade

For GPU tests, use a GPU label:

runs-on: hf-jobs-t4-small

For any GitHub Action you'd like to run on HF Jobs, this 1-line change is all you need!

To add a minimal smoke-test workflow from the CLI:

mkdir -p .github/workflows
cat > .github/workflows/hf-jobs-test.yml <<'EOF'
name: HF Jobs Test
on:
pull_request:
push:
branches: [main]
workflow_dispatch:
jobs:
test:
runs-on: hf-jobs-cpu-upgrade
steps:
- uses: actions/checkout@v4
- run: echo "Hello from Hugging Face Jobs"
EOF
git add .github/workflows/hf-jobs-test.yml
git commit -m "Run CI on Hugging Face Jobs"
git push

To verify from the CLI:

gh run list --repo YOUR-GITHUB-ORG/YOUR-REPO --limit 5
hf jobs ps --namespace "$HF_NAMESPACE"
hf spaces logs "$SPACE_ID"

You should be able to see logs just like a regular GitHub Action—for example, in this Trackio PR #565.

And that's it!

Note on choosing the right Docker image

Our first CPU setup used ubuntu:22.04

and installed missing system packages during every run. That worked, but it was slower than it needed to be. GitHub's ubuntu-latest

image includes a lot of developer tooling by default; a bare Ubuntu image does not.

For Trackio, the UI tests need Playwright browsers, Node, ffmpeg, and other tools, so optimizing the Docker image is crucial to reduce startup times.