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Waypoint-1.5: Higher-Fidelity Interactive Worlds for Everyday GPUs ALTK‑Evolve: On‑the‑Job Learning for AI Agents Safetensors is Joining the PyTorch Foundation Holo3: Breaking the Computer Use Frontier Any Custom Frontend with Gradio's Backend A New Framework for Evaluating Voice Agents (EVA) Bringing Robotics AI to Embedded Platforms: Dataset Recording, VLA Fine‑Tuning, and On‑Device Optimizations One-Shot Any Web App with Gradio's gr.HTML CUGA on Hugging Face: Democratizing Configurable AI Agents New in llama.cpp: Model Management Building Deep Research: How we Achieved State of the Art OVHcloud on Hugging Face Inference Providers 🔥 20x Faster TRL Fine-tuning with RapidFire AI Building for an Open Future - our new partnership with Google Cloud Aligning to What? Rethinking Agent Generalization in MiniMax M2 Building a Healthcare Robot from Simulation to Deployment with NVIDIA Isaac Sentence Transformers is joining Hugging Face! 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Accelerate ND-Parallel: A guide to Efficient Multi-GPU Training Vision Language Model Alignment in TRL ⚡️ Welcome GPT OSS, the new open-source model family from OpenAI! Measuring Open-Source Llama Nemotron Models on DeepResearch Bench 📚 3LM: A Benchmark for Arabic LLMs in STEM and Code Implementing MCP Servers in Python: An AI Shopping Assistant with Gradio Introducing Trackio: A Lightweight Experiment Tracking Library from Hugging Face Parquet Content-Defined Chunking TimeScope: How Long Can Your Video Large Multimodal Model Go? 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Say hello to `hf`: a faster, friendlier Hugging Face CLI ✨
Lucain Pouget, Célina Hanouti, Julien Chaumond · 2025-07-25 · via Hugging Face - Blog

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We are glad to announce a long-awaited quality-of-life improvement: the Hugging Face CLI has been officially renamed from huggingface-cli to hf!

So... why this change?

Typing huggingface-cli constantly gets old fast. More importantly, the CLI’s command structure became messy as new features were added over time (upload, download, cache management, repo management, etc.). Renaming the CLI is a chance to reorganize commands into a clearer, more consistent format.

We decided not to reinvent the wheel and instead follow a well-known CLI pattern: hf <resource> <action>. This predictable grammar makes the Hugging Face CLI more ergonomic and discoverable, while also setting the stage for upcoming features.

Getting started

To start playing with the new CLI, you’ll need to install the latest huggingface_hub version:

pip install -U huggingface_hub

and reload your terminal session. To test the install completed successfully, run hf version:

➜ hf version
huggingface_hub version: 0.34.0

Next, let’s explore the new syntax with hf --help:

➜ hf --help
usage: hf <command> [<args>]

positional arguments:
  {auth,cache,download,jobs,repo,repo-files,upload,upload-large-folder,env,version,lfs-enable-largefiles,lfs-multipart-upload}
                        hf command helpers
    auth                Manage authentication (login, logout, etc.).
    cache               Manage local cache directory.
    download            Download files from the Hub
    jobs                Run and manage Jobs on the Hub.
    repo                Manage repos on the Hub.
    repo-files          Manage files in a repo on the Hub.
    upload              Upload a file or a folder to the Hub. Recommended for single-commit uploads.
    upload-large-folder
                        Upload a large folder to the Hub. Recommended for resumable uploads.
    env                 Print information about the environment.
    version             Print information about the hf version.

options:
  -h, --help            show this help message and exit

As we can see, commands are grouped by "resource" (hf auth, hf cache, hf repo, etc.). We also surface hf upload and hf downloadat the root level since they’re expected to be the most-used commands.

To dive deeper into any command group, simply append --help:

➜ hf auth --help
usage: hf <command> [<args>] auth [-h] {login,logout,whoami,switch,list} ...

positional arguments:
  {login,logout,whoami,switch,list}
                        Authentication subcommands
    login               Log in using a token from huggingface.co/settings/tokens
    logout              Log out
    whoami              Find out which huggingface.co account you are logged in as.
    switch              Switch between access tokens
    list                List all stored access tokens

options:
  -h, --help            show this help message and exit

🔀 Migration

If you are used to huggingface-cli, most commands will look familiar. The biggest change affects authentication:

huggingface-cli login
# became
hf auth login
huggingface-cli whoami
# became
hf auth whoami
huggingface-cli logout
# became
hf auth logout

All auth commands have been grouped together with the existing hf auth switch (to switch between different local profiles) and hf auth list (to list local profiles).

The legacy huggingface-cli remains active and fully-functional. We’re keeping it around to ease the transition. If you use any command from the legacy CLI, you’ll see a warning that points you to the new CLI equivalent:

➜ huggingface-cli whoami
⚠️  Warning: 'huggingface-cli whoami' is deprecated. Use 'hf auth whoami' instead.
Wauplin
orgs:  huggingface,competitions,hf-internal-testing,templates,HF-test-lab,Gradio-Themes,autoevaluate,HuggingFaceM4,HuggingFaceH4,open-source-metrics,sd-concepts-library,hf-doc-build,hf-accelerate,HFSmolCluster,open-llm-leaderboard,pbdeeplinks,discord-community,llhf,sllhf,mt-metrics,DDUF,hf-inference,changelog,tiny-agents

One more thing... 💥 hf jobs

We couldn’t resist shipping our first dedicated command: hf jobs.

Hugging Face Jobs is a new service that lets you run any script or Docker image on Hugging Face Infrastructure using the hardware flavor of your choice. Billing is "pay-as-you-go", meaning you pay only for the seconds you use. Here’s how to launch your first command:

# Run "nvidia-smi" on an A10G GPU
hf jobs run --flavor=a10g-small ubuntu nvidia-smi

The CLI is heavily inspired by Docker’s familiar commands:

➜ hf jobs --help
usage: hf <command> [<args>] jobs [-h] {inspect,logs,ps,run,cancel,uv} ...

positional arguments:
  {inspect,logs,ps,run,cancel,uv}
                        huggingface.co jobs related commands
    inspect             Display detailed information on one or more Jobs
    logs                Fetch the logs of a Job
    ps                  List Jobs
    run                 Run a Job
    cancel              Cancel a Job
    uv                  Run UV scripts (Python with inline dependencies) on HF infrastructure

options:
  -h, --help            show this help message and exit

Learn more about Jobs by reading the guide.

Hugging Face Jobs are available only to Pro users and Team or Enterprise organizations. Upgrade your plan to get started!