From atum-ai-ml
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 compute jobs on HF infrastructure. Covers authentication, file transfers, repository creation, cache operations, and cloud compute.
npx claudepluginhub arnwaldn/atum-plugins-collection --plugin atum-ai-mlThis skill uses the workspace's default tool permissions.
The `hf` CLI provides direct terminal access to the Hugging Face Hub for downloading, uploading, and managing repositories, cache, and compute resources.
Executes pre-written implementation plans: critically reviews, follows bite-sized steps exactly, runs verifications, tracks progress with checkpoints, uses git worktrees, stops on blockers.
Dispatches parallel agents to independently tackle 2+ tasks like separate test failures or subsystems without shared state or dependencies.
Guides idea refinement into designs: explores context, asks questions one-by-one, proposes approaches, presents sections for approval, writes/review specs before coding.
The hf CLI provides direct terminal access to the Hugging Face Hub for downloading, uploading, and managing repositories, cache, and compute resources.
| 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 |
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
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
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
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
hf repo-files delete <repo_id> folder/ # Delete folder
hf repo-files delete <repo_id> "*.txt" # Delete with pattern
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
# 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
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
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
# 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 v1.0
hf 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-type: model (default), dataset, space--revision: Branch, tag, or commit hash--token: Override authentication--quiet: Output only essential info (paths/URLs)