Manage Hugging Face Hub repositories, datasets, and inference endpoints via CLI.
npx skills add https://github.com/icyzh/hermes-web --skill huggingface-hub-icyzh
Please help me install this Agent Skill. Skill: huggingface-hub Source: https://github.com/icyzh/hermes-web/tree/main/skills/mlops/huggingface-hub Command: npx skills add https://github.com/icyzh/hermes-web --skill huggingface-hub-icyzh
This skill streamlines the interaction with the Hugging Face Hub, removing the complexity of manual repository management, file synchronization, and infrastructure deployment.
Use the huggingface-hub skill to download the latest version of a specific model repository by providing its ID.
High-intent search queries and answers about installing and using this skill.
You can manage Hugging Face models and datasets from the command line by using a unified CLI to create, move, and delete repositories, as well as synchronize large files directly with the Hub.
The best way to download large model weights from the Hugging Face Hub is through automated CLI synchronization, which efficiently handles large-scale data transfers between local storage and remote repositories.
Yes, you can deploy and monitor Hugging Face Inference Endpoints via CLI commands to manage compute jobs, track resources, and scale cloud-based inference infrastructure directly.
Yes, you need authenticated access to the Hugging Face platform to perform secure write operations like uploading datasets, model weights, and managing repository lifecycle changes.
Automating Hugging Face Hub workflows via command line requires authenticated platform access for secure read and write operations, and relies entirely on CLI availability for executing end-to-end MLOps synchronization.
RheasilviaManage Hugging Face Hub repositories and sync large files.
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yuxia214Manage Hugging Face Hub models, datasets, and cloud compute jobs via CLI.
