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hugging-face-jobs

This skill should be used when users want to run any workload on Hugging Face Jobs infrastructure. Covers UV scripts, Docker-based jobs, hardware selection, cost estimation, authentication with tokens, secrets management, timeout configuration, and result persistence. Designed for general-purpose compute workloads including data processing, inference, experiments, batch jobs, and any Python-based tasks. Should be invoked for tasks involving cloud compute, GPU workloads, or when users mention running jobs on Hugging Face infrastructure without local setup.

backend/cli/skills/other/hugging-face-jobs/SKILL.md

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Nov 6, 2026
License
Apache-2.0

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# Running Workloads on Hugging Face Jobs

## Overview

Run any workload on fully managed Hugging Face infrastructure. No local setup required—jobs run on cloud CPUs, GPUs, or TPUs and can persist results to the Hugging Face Hub.

**Common use cases:**
- **Data Processing** - Transform, filter, or analyze large datasets
- **Batch Inference** - Run inference on thousands of samples
- **Experiments & Benchmarks** - Reproducible ML experiments
- **Model Training** - Fine-tune models (see `model-trainer` skill for TRL-specific training)
- **Synthetic Data Generation** - Generate datasets using LLMs
- **Development & Testing** - Test code without local GPU setup
- **Scheduled Jobs** - Automate recurring tasks