huggingface-hub
HuggingFace hf CLI: search/download/upload models, datasets.
- License 许可
- MIT
- 最近更新
- 2026-08-31
- Stars
- ★ 0
- Forks
- 0
01 前言 Front Matter
- name
- huggingface-hub
- tags
- [ "huggingface", "hf", "models", "datasets", "hub", "mlops" ]
- author
- Hugging Face
- license
- MIT
- version
- 1.0.0
- platforms
- [ "linux", "macos", "windows" ]
- description
- HuggingFace hf CLI: search/download/upload models, datasets.
03 SKILL.md 正文
Hugging Face CLI (hf) Reference Guide
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
hfcommand replaces the now deprecatedhuggingface-clicommand.
Quick Start
- Installation:
curl -LsSf https://hf.co/cli/install.sh | bash -s - Help: Use
hf --helpto view all available functions and real-world examples. - Authentication: Recommended via
HF_TOKENenvironment variable or the--tokenflag.
Core Commands
General Operations
hf download REPO_ID: Download files from the Hub.hf upload REPO_ID: Upload files/folders (recommended for single-commit).hf upload-large-folder REPO_ID LOCAL_PATH: Recommended for resumable uploads of large directories.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.
Specialized Hub Interactions
Datasets & Models
- Datasets:
hf datasets list,info, andparquet(list parquet URLs). - SQL Queries:
hf datasets sql SQL— Execute raw SQL via DuckDB against dataset parquet URLs. - Models:
hf models listandinfo. - Papers:
hf papers list— View daily papers.
Discussions & Pull Requests (hf discussions)
- Manage the lifecycle of Hub contributions:
list,create,info,comment,close,reopen, andrename. 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 uvfor running Python scripts with inline dependencies andstatsfor resource monitoring. - Spaces: Manage interactive apps. Includes
dev-modeandhot-reloadfor 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), andverify(checksum checks). - Webhooks: Automate workflows by managing Hub webhooks (
create,watch,enable/disable). - Collections: Organize Hub items into collections (
add-item,update,list).
Advanced Usage & Tips
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.
04 同仓库更多 Skills
skill-installer
Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos).
skill-creator
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.
openai-docs
Use for Codex models/pricing, scheduled tasks, skills, settings, setup, troubleshooting, customization, automations, and self-knowledge—including 'you,' 'your,' 'this app,' or 'this coding agent' when they refer to Codex—and for OpenAI APIs/products and ChatGPT Work. Also use for model choice/migration, prompting, SDKs, Responses, Realtime, agents, evals, and Chat/Work/Codex comparisons. Do not use for generic app/software tasks that merely mention Codex.
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas.
skill-creator-cc
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
prd-writing-guide
Write complete, unambiguous PRDs that development teams can implement without guesswork. Includes requirement discovery framework, structured documentation methodology, completeness checklists, and common pitfall avoidance. Use when: writing new PRDs, reviewing PRD drafts, validating requirement completeness, preparing for engineering handoff. Triggers: 'write PRD', '写PRD', '产品需求文档', '需求文档', '需求规格', '需求评审', '完善需求', 'create requirements doc', 'product requirements', 'feature spec', 'requirements document'. Anti-triggers: 'technical design doc', 'architecture design', 'implementation plan', 'API design', '架构设计', '技术方案', '实现方案', '接口设计'.