Hugging Face

Deploy and share ML models via Spaces, ZeroGPU, and API

Paid Some setup needed Web · API
platform research community builder #model-hub#datasets#ai-community

About

Deploy a model or app to Spaces and get a hosted endpoint and shareable demo without managing infrastructure. Teams use it to serve models, control data location with Storage Regions, and manage org access via SSO. Differentiators include ZeroGPU queues, a Dataset Viewer for private datasets, and clear storage and inference quotas.

Editor's Take

Worth trying if your team needs a low-friction way to publish model demos and get an API endpoint quickly; best suited for ML engineers who can invest a little time configuring org policies and quotas.

Key Features

  • Push a repo to Spaces → a hosted app and demo appear with Dev Mode
  • Upgrade to PRO → 10× private storage and 2× public storage for models and datasets
  • Run inference workloads → 20× included inference credits reduce initial hosting costs
  • Queue jobs on ZeroGPU → 8× quota and highest priority cut wait times during peaks
  • Create private datasets → preview data securely with the Dataset Viewer and choose Storage Regions for data location control

Use Cases

  • An ML engineer hosting a fine-tuned model in Spaces and exposing it via the Inference API for a pilot app
  • A data platform team enforcing SSO and Storage Regions while granting granular repo access across a 10-person org
  • A researcher sharing a private dataset with collaborators using the Dataset Viewer before publishing results

Try It Like This

  1. 1
    Deploy a model repo to Spaces

    Create a Hugging Face account → push your model or app repo to a new Space (Git-based) → Dev Mode builds a hosted demo and returns a shareable URL and endpoint for quick testing.

  2. 2
    Expose model via Inference API

    Enable the Inference API for your deployed Space or model → obtain an API token in your account settings → make a first API call (curl/SDK) to get inference responses and verify latency and output format.

  3. 3
    Enforce org access and SSO

    Create a Team/Organization in Hugging Face → configure SSO and assign repo-level roles → invite members so they can push, review, or deploy under centralized access control.

  4. 4
    Host private datasets with Dataset Viewer

    Upload a private dataset and select a Storage Region → open the Dataset Viewer to preview examples securely → share viewer access with collaborators before publishing or exporting data.

  5. 5
    Run queued jobs on ZeroGPU

    Submit batch inference jobs to a Space and select the ZeroGPU queue option → monitor job queue and priority in the dashboard → leverage included inference credits to reduce initial hosting costs and cut wait times during peaks.

Pros & Cons

Pros

  • Intuitive web UX and Dev Mode reduce onboarding time for getting a hosted demo from a repo.
  • Robust API surface (Spaces + Inference API) enables programmatic integration and direct inference calls from apps.
  • Controls for private datasets and Storage Regions plus a Dataset Viewer let teams preview data securely and choose data location.

Cons

  • Users report pricing transparency can be unclear at larger scale, making long-term cost planning harder.
  • Occasional performance degradation has been reported during traffic peaks, which can affect latency-sensitive apps.
  • Advanced features (fine-grained quotas, ZeroGPU queues, organization policies) require a learning curve to configure optimally.

Getting Started

  1. 1 Create an account on huggingface.co and choose a plan (PRO, Team, or Enterprise).
  2. 2 Create a Space from a template or repo, or upload a model/dataset to your org.
  3. 3 Open the Space URL and run a test inference via the API to confirm your deployment works.

Pricing

PlanPriceIncludes
PRO$9 per month10× private storage, 2× public storage, 20× included inference credits, 8× ZeroGPU quota & highest queue priority, Spaces Dev Mode & ZeroGPU Spaces hosting, Personal blog publishing, Dataset Viewer for private datasets, PRO badge
Team$20 per user per monthSSO (SAML & OIDC), Storage Regions, Audit Logs, Resource Groups, Repository Analytics, Advanced auth and visibility controls, Centralized token control, Dataset Viewer for private datasets, Advanced compute for Spaces, ZeroGPU & Inference Providers PRO benefits
EnterpriseStarting at $50 per user per monthAll Team benefits, highest storage/bandwidth/API limits, SCIM provisioning, advanced security/access controls, managed billing with annual commitments, legal/compliance processes, dedicated support

Similar Tools

FAQ

Is Hugging Face free?

It is a paid service.

What platforms is Hugging Face available on?

Available on Web, API.

Does Hugging Face support Korean?

Korean is not currently supported.

Helpful?