Migrating Your GitHub CI to Hugging Face Jobs

Summary

Trackio's GitHub Actions CI was limited by generic hosted machines, maintenance-related delays, and lack of readily available GPU runners, while the project needed CPU checks and CUDA-based tests. The setup keeps GitHub Actions as the CI coordinator and uses a dispatcher Space plus the huggingface/jobs-actions bridge to launch ephemeral GitHub runners inside Hugging Face Jobs, selected through labels such as hf-jobs-cpu-upgrade and hf-jobs-t4-small. The guide covers duplicating and configuring the dispatcher, creating a GitHub App, supplying runner credentials and an HF token, changing runs-on, choosing Docker images, and validating runs and logs; Playwright and NVIDIA CUDA images are used for CPU and GPU examples. In Trackio, the CPU job took 1m10s versus a 1m40s GitHub ubuntu-latest baseline, while the GPU check passed in 45s and cost less than a cent at the t4-small rate; logs were available through both systems.

Takeaways

1. 1

   Changing a workflow from runs-on: ubuntu-latest to labels such as hf-jobs-cpu-upgrade or hf-jobs-t4-small routes the job to Hugging Face Jobs through the dispatcher.

2. 2

   Trackio's CPU job using the Microsoft Playwright image ran in 1m10s, compared with 1m40s for the GitHub ubuntu-latest baseline, an improvement of about 30%.

3. 3

   Trackio's GPU check ran on a t4-small Hugging Face Job, passed in 45 seconds, and cost less than a cent for that duration; Hugging Face Job logs can also be fetched with the CLI.