Manage Hugging Face Hub repositories for models, datasets, and Spaces.
npx skills add https://github.com/MarbleSodas/Mavis --skill huggingface-hub-marblesodas
Please help me install this Agent Skill. Skill: huggingface-hub Source: https://github.com/MarbleSodas/Mavis/tree/main/skills/mlops/huggingface-hub Command: npx skills add https://github.com/MarbleSodas/Mavis --skill huggingface-hub-marblesodas
It helps you search, download, and publish Hugging Face Hub assets without manually browsing pages or stitching together multiple tools.
Upload a local folder to your Hugging Face repository in one step by running: upload-large-folder your-org/your-repo ./local-folder
High-intent search queries and answers about installing and using this skill.
To upload a large folder to the Hugging Face Hub, use the modern hf CLI command `upload-large-folder` with your target repository and local directory path to sync artifacts efficiently.
Yes, you can automate Hugging Face model management and storage syncing by using supported hf CLI subcommands that provide JSON output for machine-readable workflows.
Managing Hugging Face inference endpoints and jobs is handled directly through the hf CLI, which provides subcommands to deploy compute infrastructure and operate automation features.
Yes, maintaining Hugging Face repositories for models, datasets, and Spaces requires the modern hf CLI to execute supported subcommands for repository lifecycle operations.
Hugging Face Hub authentication is managed through the hf CLI, which handles auth subcommands to enable secure downloading, uploading, and publishing of ML workflow artifacts.
john-data-chenManage Hugging Face Hub repositories, models, and datasets via the hf CLI.
growthxaiIdentify Output workflow runs by ID and compute their LLM token and service costs.
bugrabilgeExecute Hugging Face Hub operations via the hf CLI for models, datasets, and repositories.
ldzhhxxManage models and datasets on Hugging Face Hub using the Hugging Face CLI.
