GitHub Actions

Prerequisites

Add your Badgr API key as a repository secret named BADGR_API_KEY:

1. Go to your repository Settings → Secrets and variables → Actions
2. Click New repository secret
3. Name: BADGR_API_KEY, Value: your Badgr API key

Run a GPU job

Use badgr-run to run any container command on a GPU. The action waits for completion and streams logs to the workflow output.

- name: Run training job
  uses: badgr/badgr-run@v1
  with:
    api_key: ${{ secrets.BADGR_API_KEY }}
    gpu: A100
    command: python train.py --epochs 10
    max_cost: "10"

The action uses the checked-out repo as the source (equivalent to badgr run . --cmd "..."). No Docker build required.

Serve a model endpoint

Use badgr-serve to provision an OpenAI-compatible endpoint for the duration of your workflow. The endpoint tears down automatically when the job finishes.

- name: Serve model
  id: serve
  uses: badgr/badgr-serve@v1
  with:
    api_key: ${{ secrets.BADGR_API_KEY }}
    model: Qwen/Qwen2.5-7B-Instruct
    gpu: L40S

- name: Run evals
  run: python eval.py --base-url ${{ steps.serve.outputs.endpoint_url }}

Full workflow example

name: GPU Training

on:
  push:
    branches: [main]

jobs:
  train:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - name: Run training job
        uses: badgr/badgr-run@v1
        with:
          api_key: ${{ secrets.BADGR_API_KEY }}
          gpu: A100
          command: python train.py --epochs 10
          max_cost: "20"
          timeout_minutes: 120

Badgr uploads the checked-out repo, installs deps, runs the command, and streams logs to the workflow. No Docker build step needed.

badgr-run inputs

badgr-serve inputs