Loading...
Loading...
Execute Hugging Face Hub operations using the `hf` CLI. Use when the user needs to download models/datasets/spaces, upload files to Hub repositories, create repos, manage local cache, or run comput...
npx skill4agent add sickn33/antigravity-awesome-skills hugging-face-clihf| Task | Command |
|---|---|
| Login | |
| Download model | |
| Download to folder | |
| Upload folder | |
| Create repo | |
| Create tag | |
| Delete files | |
| List cache | |
| Remove from cache | |
| List models | |
| Get model info | |
| List datasets | |
| Get dataset info | |
| List spaces | |
| Get space info | |
| List endpoints | |
| Run GPU job | |
| Environment info | |
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 outhf 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 versionhf 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 messagehf 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 taghf repo-files delete <repo_id> folder/ # Delete folder
hf repo-files delete <repo_id> "*.txt" # Delete with patternhf 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# 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 infohf 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 jobhf 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 endpointcpu-basiccpu-upgradecpu-xlt4-smallt4-mediuml4x1l4x4l40sx1l40sx4l40sx8a10g-smalla10g-largea10g-largex2a10g-largex4a100-largeh100h100x8# 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)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 v1.0hf upload my-username/my-space . . --repo-type space \
--exclude="logs/*" --delete="*" --commit-message="Sync"hf cache ls # See all cached repos and sizes
hf cache rm model/gpt2 # Remove a repo from cache--repo-typemodeldatasetspace--revision--token--quiet