Hugging Face CLI

Manage Hugging Face Hub via hf CLI. Use when working with HF AI models, datasets, spaces, or repos.

Hugging Face (https://huggingface.co) is the leading platform for sharing and collaborating on AI models, datasets, and spaces. This skill enables interaction with the Hub through the official hf CLI.

Installation

Check if hf is available by running hf version. If not installed:

pip install -U "huggingface_hub[cli]"
# or
brew install hf

If the options above do not work, follow the official installation guide.

After installation, run hf version to verify. If the command is not found, run source ~/.bashrc (or source ~/.zshrc for zsh) to reload the PATH, then try again.

Authentication

A Hugging Face User Access Token is required. The token is provided via the HF_TOKEN environment variable.

If authentication fails or the token is missing, instruct the user to:

1. Go to https://huggingface.co/settings/tokens
2. Create a new token — there are two permission levels:
   • Read (safer): sufficient for searching, downloading models/datasets, listing repos, browsing papers, and most read-only operations. Choose this if you only need to explore and download.
   • Write (less safe, broader access): required for creating/deleting repos, uploading files, managing discussions, deploying endpoints, and running jobs. Example 3 (create a repo and upload weights) requires a write token.
3. Set it as an environment variable: export HF_TOKEN="hf_..." (add to shell profile for persistence)

Important: Do NOT run hf auth login interactively — it requires terminal input. Instead, use the environment variable directly. The hf CLI automatically picks up HF_TOKEN from the environment for all commands. To verify authentication, run:

hf auth whoami

Key Commands

Task	Command
Check current user	hf auth whoami
Download files	hf download <repo_id> [files...] [--local-dir <path>]
Download specific revision	hf download <repo_id> --revision <branch|tag|commit>
Download with filters	hf download <repo_id> --include "*.safetensors" --exclude "*.bin"
Upload files	hf upload <repo_id> <local_path> [path_in_repo]
Upload as PR	hf upload <repo_id> <local_path> [path_in_repo] --create-pr
Upload (private repo)	hf upload <repo_id> <local_path> [path_in_repo] --private
Upload large folder	hf upload-large-folder <repo_id> <local_path>
Create a repo	hf repos create <name> [--repo-type model|dataset|space] [--private]
Delete a repo	hf repos delete <repo_id>
Delete files from repo	hf repos delete-files <repo_id> <path>...
Duplicate a repo	hf repos duplicate <repo_id> [--type model|dataset|space]
Repo settings	hf repos settings <repo_id> [--private|--public]
Manage branches	hf repos branch create|delete <repo_id> <branch>
Manage tags	hf repos tag create|delete <repo_id> <tag>
List models	hf models ls [--search <query>] [--sort downloads] [--limit N]
Model info	hf models info <repo_id>
List datasets	hf datasets ls [--search <query>]
Dataset info	hf datasets info <repo_id>
Run SQL on data	hf datasets sql "<SQL>"
List spaces	hf spaces ls [--search <query>]
Space info	hf spaces info <repo_id>
Space dev mode	hf spaces dev-mode <repo_id>
List papers	hf papers ls [--limit N]
List collections	hf collections ls [--owner <user>] [--sort trending]
Create collection	hf collections create "<title>"
Collection info	hf collections info <collection_slug>
Add to collection	hf collections add-item <collection_slug> <repo_id> <type>
Delete collection	hf collections delete <collection_slug>
Run a cloud job	hf jobs run <docker_image> <command>
List jobs	hf jobs ps
Job logs	hf jobs logs <job_id>
Cancel a job	hf jobs cancel <job_id>
Job hardware	hf jobs hardware
Deploy endpoint	hf endpoints deploy <name> --repo <repo_id> --framework <fw> --accelerator <hw> ...
List endpoints	hf endpoints ls
Endpoint info	hf endpoints describe <name>
Pause/resume endpoint	hf endpoints pause|resume <name>
Delete endpoint	hf endpoints delete <name>
List discussions	hf discussions ls <repo_id>
Create discussion	hf discussions create <repo_id> --title "<title>"
Comment on discussion	hf discussions comment <repo_id> <num> --body "<text>"
Close discussion	hf discussions close <repo_id> <num>
Merge PR	hf discussions merge <repo_id> <num>
Manage cache	hf cache ls, hf cache rm <id>, hf cache prune
Delete bucket / files	hf buckets delete <user>/<bucket>, hf buckets rm <user>/<bucket>/<path>
Sync to bucket	hf sync <local_path> hf://buckets/<user>/<bucket>
Print environment	hf env

End-to-End Examples

Example 1: Explore trending models, pick one, and preview a download

hf models ls --sort trending_score --limit 5
hf models info openai-community/gpt2
hf download --dry-run openai-community/gpt2 config.json tokenizer.json
hf download openai-community/gpt2 config.json tokenizer.json --local-dir ./gpt2

Example 2: Browse today's papers and find related datasets

hf papers ls --limit 5
hf datasets ls --search "code" --sort downloads --limit 5
hf datasets info bigcode/the-stack

Example 3: Create a private model repo and upload weights

hf repos create my-fine-tuned-model --private
# create returns <your-username>/my-fine-tuned-model — use that full ID below
hf upload <username>/my-fine-tuned-model ./output --commit-message "Add fine-tuned weights"
hf repos tag create <username>/my-fine-tuned-model v1.0 -m "Initial release"

Further Reference

Reference version: hf CLI v1.x

For the full list of commands and options, use built-in help:

hf --help
hf <command> --help

• Full documentation: https://huggingface.co/docs/huggingface_hub/guides/cli
• CLI reference: https://huggingface.co/docs/huggingface_hub/package_reference/cli

Safety Rules

• Destructive commands require explicit user confirmation. Before running any of the following, describe what will happen and ask the user to confirm:
  • hf repos delete — permanently deletes a repository
  • hf repos delete-files — deletes files from a repository
  • hf buckets delete / hf buckets rm — deletes buckets or bucket files
  • hf discussions close / hf discussions merge — closes or merges PRs/discussions
  • hf collections delete — permanently deletes a collection
  • hf endpoints delete — permanently deletes an Inference Endpoint
  • hf jobs cancel — cancels a running compute job
  • Any command with --delete flag (e.g., sync with deletion)
  • hf cache rm / hf cache prune — removes cached data from disk (re-downloadable, but may waste bandwidth)
• Never expose or log the HF_TOKEN value. Do not include it in command output or commit it to files.
• When uploading, warn the user if the target repo is public and the upload may contain sensitive data.