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

For model training specifically: See the model-trainer skill for TRL-based training workflows.

When to Use This Skill