hugging-face-jobs

You can run compute jobs on Hugging Face infrastructure using UV scripts or Docker-based jobs for data processing and batch inference. This approach handles hardware selection, cost estimation, and pushes outputs back to the Hub for durable results.

Yes, Hugging Face Jobs supports GPU hardware selection and cost estimation to optimize performance versus cost. You can specify hardware for cloud compute tasks like experiments and batch jobs to balance your computational requirements with infrastructure expenses.

You handle token authentication securely for Hugging Face cloud compute tasks by enforcing secure token usage via secrets. This method manages authentication workflows safely, ensuring your Hugging Face tokens remain protected during data processing and batch inference jobs.

Yes, you can use Docker-based jobs for batch inference and synthetic data generation on Hugging Face. The platform supports diverse compute workloads, allowing you to containerize experiments and data processing pipelines while ensuring result persistence back to the Hub.

The best way to persist results from Hugging Face Jobs back to the Hub is through built-in result persistence workflows. This ensures durable outputs from your cloud compute tasks, automatically pushing data processing and inference results back to your Hugging Face repository.