huggingface-jobs

Run workloads on Hugging Face Jobs using UV scripts or Docker configurations that enforce secure HF_TOKEN integration and secrets management, ensuring credentials remain protected during cloud execution.

Yes, Hugging Face Jobs supports batch inference and model fine-tuning by selecting per-job GPU or TPU hardware flavors, configuring dependencies, and setting timeouts for compute workloads.

Persist results from Hugging Face Jobs to the Hub by utilizing hub-based persistence mechanisms like push_to_hub or API calls, saving processed data and inference outputs directly to your repository.

Yes, Hugging Face Jobs supports UV scripts and Docker-based configurations for data processing, allowing custom dependency management, hardware flavor selection, and execution timeouts for diverse workloads.

Handle secrets carefully when running cloud computing jobs on Hugging Face to prevent unauthorized credential access, enforcing secure token management through dedicated secrets integration and HF_TOKEN environment configuration.

Limitations of running arbitrary workloads on Hugging Face Jobs include managing per-job timeouts, explicit CPU/GPU/TPU hardware flavor selection constraints, and the necessity to configure dependencies correctly for successful execution.