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Huggingface Hub

HuggingFace hf CLI: search/download/upload models, datasets

BundledHermes skill
Last registry verification2026-08-18v1.0.1Hugging Face
Open original source ↗اقرأ بالعربية
Plain meaning

What does it add to Hermes?

HuggingFace hf CLI: search/download/upload models, datasets

Huggingface Hub is a skill related to research and sources. It gives the agent a way to find external information and sources instead of relying only on model memory.

This plain-language explanation is based on the publisher description. The original text remains visible for verification.

Use it when

Use it when your goal in research and sources is clear and you can limit it to the data and actions it actually needs.

Skip it when

Do not add it merely to experiment when Hermes already has a simpler path, or when you cannot review its source and permissions.

Who is it for?

Best for users who want a repeatable way of working inside Hermes.

Safe first test

Ask for one recent fact with two sources, then open both links and verify dates and evidence.

Original publisher description

HuggingFace hf CLI: search/download/upload models, datasets

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Data source

This entry was indexed from Hermes Bundled Skills. Our explanation interprets the type and domain without inventing a capability not present upstream.

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Security review

The source is official or editorially reviewed, but you still need to review permissions and version compatibility.

Safe setup path

Inspect, install, then test.

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    Open the source

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  2. 02
    Review permissions and secrets

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Setup method

Already installed with Hermes.

This skill ships with Hermes and loads when the agent decides it is relevant. There is nothing to install; read the definition below so you know what it will do.

Open the official page ↗
The full skill definition

Exactly what Hermes loads when this skill runs.

Reproduced from the official documentation. Read it before enabling the skill: this text becomes the agent's instructions.

HuggingFace hf CLI: search/download/upload models, datasets.

Skill metadata

A lookup table. Do not read it all; find the row that applies to you.

SourceBundled (installed by default)
Pathskills/mlops/huggingface-hub
Version1.0.1
AuthorHugging Face
LicenseMIT
Platformslinux, macos, windows

Reference: full SKILL.md

Explains the idea itself. Read it slowly; the later sections build on it.

The hf command is the modern command-line interface for interacting with the Hugging Face Hub, providing tools to manage repositories, models, datasets, and Spaces.

IMPORTANT: The hf command replaces the now deprecated huggingface-cli command.

Quick Start

Ordered, practical steps. Run one and confirm it worked before moving on.

  • Installation: curl -LsSf https://hf.co/cli/install.sh | bash -s
  • Help: Use hf --help to view all available functions and real-world examples.
  • Authentication: Recommended via HF_TOKEN environment variable or the --token flag.

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Core Commands

Explains the idea itself. Read it slowly; the later sections build on it.

General Operations

  • hf download REPO_ID: Download files from the Hub.
  • hf upload REPO_ID: Upload files/folders (recommended for single-commit; also handles resumable uploads of large directories).
  • hf upload-large-folder REPO_ID LOCAL_PATH: [Deprecated] — use hf upload instead.
  • hf sync: Sync files between a local directory and a bucket.
  • hf env / hf version: View environment and version details.

Authentication (hf auth)

  • login / logout: Manage sessions using tokens from huggingface.co/settings/tokens ↗.
  • list / switch: Manage and toggle between multiple stored access tokens.
  • whoami: Identify the currently logged-in account.

Repository Management (hf repos)

  • create / delete: Create or permanently remove repositories.
  • duplicate: Clone a model, dataset, or Space to a new ID.
  • move: Transfer a repository between namespaces.
  • branch / tag: Manage Git-like references.
  • delete-files: Remove specific files using patterns.

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Specialized Hub Interactions

Explains the idea itself. Read it slowly; the later sections build on it.

Datasets & Models

  • Datasets: hf datasets list, info, and parquet (list parquet URLs).
  • SQL Queries: hf datasets sql SQL — Execute raw SQL via DuckDB against dataset parquet URLs.
  • Models: hf models list and info.
  • Papers: hf papers ls — View daily papers.

Discussions & Pull Requests (hf discussions)

  • Manage the lifecycle of Hub contributions: list, create, info, comment, close, reopen, and rename.
  • diff: View changes in a PR.
  • merge: Finalize pull requests.

Infrastructure & Compute

  • Endpoints: Deploy and manage Inference Endpoints (deploy, pause, resume, scale-to-zero, catalog).
  • Jobs: Run compute tasks on HF infrastructure. Includes hf jobs uv for running Python scripts with inline dependencies and stats for resource monitoring.
  • Spaces: Manage interactive apps. Includes dev-mode and hot-reload for Python files without full restarts.

Storage & Automation

  • Buckets: Full S3-like bucket management (create, cp, mv, rm, sync).
  • Cache: Manage local storage with list, prune (remove detached revisions), and verify (checksum checks).
  • Webhooks: Automate workflows by managing Hub webhooks (create, watch, enable/disable).
  • Collections: Organize Hub items into collections (add-item, update, list).

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Advanced Usage & Tips

Explains the idea itself. Read it slowly; the later sections build on it.

Global Flags

  • --format json: Produces machine-readable output for automation.
  • -q / --quiet: Limits output to IDs only.

Extensions & Skills

  • Extensions: Extend CLI functionality via GitHub repositories using hf extensions install REPO_ID.
  • Skills: Manage AI assistant skills with hf skills add.