hugging-face-cli
The hf CLI provides direct terminal access to the Hugging Face Hub for downloading, uploading, and managing repositories, cache, and compute resources.
- risk
- safe
- date added
- 2026-02-27
Hugging Face CLI
The hf CLI provides direct terminal access to the Hugging Face Hub for downloading, uploading, and managing repositories, cache, and compute resources.
When to Use This Skill
Use this skill when:
- User needs to download models, datasets, or spaces
- Uploading files to Hub repositories
- Creating Hugging Face repositories
- Managing local cache
- Running compute jobs on HF infrastructure
- Working with Hugging Face Hub authentication
Quick Command Reference
| Task | Command |
|---|---|
| Login | hf auth login |
| Download model | hf download <repo_id> |
| Download to folder | hf download <repo_id> --local-dir ./path |
| Upload folder | hf upload <repo_id> . . |
| Create repo | hf repo create <name> |
| Create tag | hf repo tag create <repo_id> <tag> |
| Delete files | hf repo-files delete <repo_id> <files> |
| List cache | hf cache ls |
| Remove from cache | hf cache rm <repo_or_revision> |
| List models | hf models ls |
| Get model info | hf models info <model_id> |
| List datasets | hf datasets ls |
| Get dataset info | hf datasets info <dataset_id> |
| List spaces | hf spaces ls |
| Get space info | hf spaces info <space_id> |
| List endpoints | hf endpoints ls |
| Run GPU job | hf jobs run --flavor a10g-small <image> <cmd> |
| Environment info | hf env |
Core Commands
Authentication
hf auth login # Interactive login hf auth login --token $HF_TOKEN # Non-interactive hf auth whoami # Check current user hf auth list # List stored tokens hf auth switch # Switch between tokens hf auth logout # Log out
Download
hf download <repo_id> # Full repo to cache hf download <repo_id> file.safetensors # Specific file hf download <repo_id> --local-dir ./models # To local directory hf download <repo_id> --include "*.safetensors" # Filter by pattern hf download <repo_id> --repo-type dataset # Dataset hf download <repo_id> --revision v1.0 # Specific version
Upload
hf upload <repo_id> . . # Current dir to root hf upload <repo_id> ./models /weights # Folder to path hf upload <repo_id> model.safetensors # Single file hf upload <repo_id> . . --repo-type dataset # Dataset hf upload <repo_id> . . --create-pr # Create PR hf upload <repo_id> . . --commit-message="msg" # Custom message
Repository Management
hf repo create <name> # Create model repo hf repo create <name> --repo-type dataset # Create dataset hf repo create <name> --private # Private repo hf repo create <name> --repo-type space --space_sdk gradio # Gradio space hf repo delete <repo_id> # Delete repo hf repo move <from_id> <to_id> # Move repo to new namespace hf repo settings <repo_id> --private true # Update repo settings hf repo list --repo-type model # List repos hf repo branch create <repo_id> release-v1 # Create branch hf repo branch delete <repo_id> release-v1 # Delete branch hf repo tag create <repo_id> v1.0 # Create tag hf repo tag list <repo_id> # List tags hf repo tag delete <repo_id> v1.0 # Delete tag
Delete Files from Repo
hf repo-files delete <repo_id> folder/ # Delete folder hf repo-files delete <repo_id> "*.txt" # Delete with pattern
Cache Management
hf cache ls # List cached repos hf cache ls --revisions # Include individual revisions hf cache rm model/gpt2 # Remove cached repo hf cache rm <revision_hash> # Remove cached revision hf cache prune # Remove detached revisions hf cache verify gpt2 # Verify checksums from cache
Browse Hub
# Models hf models ls # List top trending models hf models ls --search "MiniMax" --author MiniMaxAI # Search models hf models ls --filter "text-generation" --limit 20 # Filter by task hf models info MiniMaxAI/MiniMax-M2.1 # Get model info # Datasets hf datasets ls # List top trending datasets hf datasets ls --search "finepdfs" --sort downloads # Search datasets hf datasets info HuggingFaceFW/finepdfs # Get dataset info # Spaces hf spaces ls # List top trending spaces hf spaces ls --filter "3d" --limit 10 # Filter by 3D modeling spaces hf spaces info enzostvs/deepsite # Get space info
Jobs (Cloud Compute)
hf jobs run python:3.12 python script.py # Run on CPU hf jobs run --flavor a10g-small <image> <cmd> # Run on GPU hf jobs run --secrets HF_TOKEN <image> <cmd> # With HF token hf jobs ps # List jobs hf jobs logs <job_id> # View logs hf jobs cancel <job_id> # Cancel job
Inference Endpoints
hf endpoints ls # List endpoints hf endpoints deploy my-endpoint \ --repo openai/gpt-oss-120b \ --framework vllm \ --accelerator gpu \ --instance-size x4 \ --instance-type nvidia-a10g \ --region us-east-1 \ --vendor aws hf endpoints describe my-endpoint # Show endpoint details hf endpoints pause my-endpoint # Pause endpoint hf endpoints resume my-endpoint # Resume endpoint hf endpoints scale-to-zero my-endpoint # Scale to zero hf endpoints delete my-endpoint --yes # Delete endpoint
GPU Flavors: cpu-basic, cpu-upgrade, cpu-xl, t4-small, t4-medium, l4x1, l4x4, l40sx1, l40sx4, l40sx8, a10g-small, a10g-large, a10g-largex2, a10g-largex4, a100-large, h100, h100x8
Common Patterns
Download and Use Model Locally
# Download to local directory for deployment hf download meta-llama/Llama-3.2-1B-Instruct --local-dir ./model # Or use cache and get path MODEL_PATH=$(hf download meta-llama/Llama-3.2-1B-Instruct --quiet)
Publish Model/Dataset
hf repo create my-username/my-model --private hf upload my-username/my-model ./output . --commit-message="Initial release" hf repo tag create my-username/my-model v1.0
Sync Space with Local
hf upload my-username/my-space . . --repo-type space \ --exclude="logs/*" --delete="*" --commit-message="Sync"
Check Cache Usage
hf cache ls # See all cached repos and sizes hf cache rm model/gpt2 # Remove a repo from cache
Key Options
--repo-type:model(default),dataset,space--revision: Branch, tag, or commit hash--token: Override authentication--quiet: Output only essential info (paths/URLs)
References
- Complete command reference: See references/commands.md
- Workflow examples: See references/examples.md