EUAlternatives
    H

    Hugging Face

    The AI community platform for models, datasets, and machine learning collaboration.

    FRFrance
    Headquarters
    🇫🇷France
    Data Hosting
    EU-based
    Structure
    Independent
    Compliance
    â–£GDPRâ—†EU HQ

    Hugging Face key facts

    Last updated
    Headquarters
    France (FR)
    Ownership
    Independent
    Deployment
    SaaS
    Open source
    No
    US Cloud Act exposure
    Low (no US parent)
    Replaces
    AWS SageMaker, Google Vertex AI, Azure ML

    About Hugging Face

    Hugging Face is a community platform where machine learning practitioners host, share, and collaborate on models, datasets, and applications. Users can browse millions of public models and hundreds of thousands of datasets, and publish interactive ML apps via Spaces to showcase work and build their profiles. Beyond the open community hub, Hugging Face offers paid capabilities for teams and enterprises, including single sign-on, regional controls, priority support, audit logs, resource groups, and private dataset viewers. The platform also provides unified access to tens of thousands of models via an Inference Providers API with no service fees, and managed compute through Inference Endpoints and GPU upgrades for Spaces. An extensive open‑source stack (e.g., Transformers, Diffusers, Tokenizers, Datasets, TGI, Accelerate) underpins the ecosystem.

    Alternative to

    AWS SageMakerGoogle Vertex AIAzure ML

    Target Segments

    Other

    Deployment Options

    SaaS

    Key Features

    Host and collaborate on public models, datasets, and applications
    Spaces: publish and explore interactive AI applications
    Browse 2M+ models and 500k+ datasets
    Team & Enterprise features: Single Sign-On, Regions, Priority Support, Audit Logs, Resource Groups, Private Datasets Viewer
    Inference Providers: unified API to access 45,000+ models with no service fees
    Compute: deploy on optimized Inference Endpoints
    GPU upgrades for Spaces applications
    Open-source ML libraries including Transformers, Diffusers, Safetensors, Tokenizers, TRL, Datasets, TGI, and Accelerate

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