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CI/CD Orchestration with Hugging Face Jobs

2 posts · Jun 2026

What this trail covers

Hugging Face Jobs provides a robust platform for orchestrating CI/CD workflows, enabling seamless migration from existing CI systems like GitHub Actions. This includes features for dispatching jobs, managing execution environments, and integrating with code repositories. The platform now supports running vLLM servers with a single command, enabling users to spin up private, OpenAI-compatible LLM endpoints on Hugging Face infrastructure without provisioning servers or Kubernetes. This includes fe

All Hugging Face trails
  1. Run a vLLM Server on HF Jobs in One CommandThis post details how to run a vLLM server on Hugging Face Jobs with a single command, leveraging the `hf jobs run` CLI. It covers launching the server with specific GPU flavors, exposing ports, and querying the endpoint using cURL or the OpenAI Python client. It also provides guidance on scaling to larger models with tensor parallelism, setting up a Gradio UI for chat interactions, enabling SSH access for debugging, and using the endpoint as a backend for coding agents with Pi. The post contrasts HF Jobs with Inference Endpoints for different use cases.
  2. Migrating Your GitHub CI to Hugging Face JobsThis post details the migration of GitHub CI workflows to Hugging Face Jobs, focusing on the `jobs-actions-dispatcher` for running GitHub Actions on Hugging Face infrastructure. It highlights the benefits of this migration for users looking to leverage Hugging Face's CI/CD capabilities, including simplified setup and execution of CI pipelines.