huggingface-hub

You can manage Hugging Face Hub repositories by creating, duplicating, and moving models or datasets directly from your terminal. This removes the complexity of manual repository management and streamlines infrastructure deployment.

To upload large files to a Hugging Face dataset repository, you can use built-in support for resumable transfers. This allows you to efficiently download, upload, and sync large files or entire datasets without manual synchronization.

Yes, you can run machine learning compute jobs on Hugging Face infrastructure directly. The skill supports managing Inference Endpoints and executing cloud-based compute jobs without requiring you to leave your current workflow environment.

Yes, authenticated access to the Hugging Face platform is required. You must provide valid credentials to perform administrative tasks, data transfers, and repository versioning for models and datasets.

The best way to sync local machine learning models with the Hugging Face Hub is through large-scale file synchronization. This process supports repository versioning and resumable transfers to ensure your local models match the remote hub.