Hub documentation
Examples & Tutorials
Examples & Tutorials
Train models
The launch commands for Transformers, TRL, Unsloth and Axolotl are on Train Models on Jobs. Each one links to the library’s own guide.
Process data at scale
DataTrove provides an experimental JobsPipelineExecutor for distributing data processing pipelines across a pool of Jobs. It supports concurrency limits, multi-stage dependencies, retries, and resumable runs — re-running a pipeline skips tasks that already completed and only runs the remaining ones.
See the ready-to-run examples for:
UV Scripts
The uv-scripts organization maintains a collection of self-contained uv scripts that run on Jobs with a single command. Scripts cover OCR, batch inference, text classification, object detection, dataset statistics, embedding visualization, and more.
Unsloth also provides ready-to-run training scripts for fine-tuning LLMs and VLMs on Jobs.
Coding Agent Skills
Coding agents like Claude Code, Codex and Cursor can submit and monitor Jobs for you. Install the hf CLI skill, generated from your installed CLI so it stays current:
hf skills add
See Hugging Face CLI for AI agents for setup per agent, and Agent Skills for training and other workflow skills.
Sandboxes
The expose ports feature of Jobs makes them a great fit for building sandboxes, i.e. temporary self-contained environments used by agents and LLM applications.
Community Tutorials and Projects
- Train on massive datasets without downloading - Stream datasets directly on Jobs with Unsloth, no local storage needed
- Fine-tune a vision-language model with TRL - Fine-tune Qwen2.5-VL for art history tasks using TRL and Jobs
- FreeFlow - Open-source annotation platform with built-in Jobs integration for training YOLOv11 object detection models
- hfdask - Run Dask programs across CPU and GPU Jobs from one YAML cluster definition, with mTLS between nodes and automatic cleanup
Have a tutorial or project using Jobs? Open a PR to add it here.
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