Hugging Face

Ever wondered where the world's AI models and datasets live?

Automated product research from public website content. No hands-on app test is recorded for this profile. Pricing source and check date are shown below where available.

Research fitSource-based assessment: Hugging Face is the essential hub for the open-source machine learning community, offering unparalleled access to models, datasets, and deployment tools for AI development.

Hugging Face provides a comprehensive platform for machine learning, offering access to a vast repository of models, datasets, and tools. It facilitates collaboration, experimentation, and deployment of AI applications, from personal projects to enterprise solutions.

Visit Hugging Face
Screenshot of Hugging FaceVisit Hugging Face
Key Features:
  • Vast Model Hub with pre-trained models
  • Extensive Dataset Hub for various tasks
  • Spaces for hosting and sharing ML applications
  • Inference Endpoints for dedicated model deployment
  • Storage Buckets for AI assets
Pros
  • Machine learning engineers needing a collaborative platform
  • Researchers looking for pre-trained models and datasets
  • Developers deploying AI applications with scalable infrastructure
Cons
  • Pricing for advanced hardware and storage can add up for heavy usage.
  • Some features like Resource Groups and SCIM provisioning are exclusive to Enterprise plans.
  • Refunds for PRO subscriptions are not automated and require direct email contact.
Pricing
freemiumFree tier
Starting at:$9/month
Free tier:Limited storage, inference credits, and ZeroGPU quota. Basic CPU for Spaces.
Plans
  • PRO Account: $9/month (personal)
  • Team: $20/month per user
  • Enterprise: $50/month per user
Refund:Contact support for PRO subscription refunds
Categories:
AI InfrastructureCode & DevelopmentResearch & Science
Tags:
machine learningdeep learningmodelsdatasetsAI deploymentopen sourceGPUinferencetraining
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Quick Decision
Try if: You are an ML practitioner, researcher, or developer looking for a comprehensive, collaborative, and scalable platform to build, share, and deploy AI models and applications.
Skip if: You need a simple, no-code solution for basic AI tasks or prefer to manage all infrastructure and billing directly with cloud providers.
Not for: Users seeking simple, no-code AI solutions; Individuals with no prior machine learning experience
Trust Signals

  • Team Size

    large
Tech Details
Platforms
webapi
Integrations
GitHub Actions
Open Source
Yes
Support
Channels
emailforumGitHub issuesDiscord
Company

  • Name

    Hugging Face

Hugging Face is an AI company that builds tools and platforms for machine learning, with a focus on open-source contributions and community collaboration.

FAQ

What is Hugging Face PRO and what does it offer?

Hugging Face PRO is a personal account upgrade for $9/month, offering 10x private storage, 2x public storage, 20x inference credits, 8x ZeroGPU quota, Spaces Dev Mode, personal blog publishing, and a PRO badge.

How does Hugging Face handle billing for Inference Providers?

Hugging Face offers pay-as-you-go pricing for Inference Providers, with monthly credits for all users. You can choose to route requests through Hugging Face (billed by HF, credits apply) or use your own custom provider key (billed directly by the provider, no HF credits).

Can I get a refund for my Hugging Face PRO subscription?

Refunds for PRO subscriptions are not automatically processed. You need to contact Hugging Face support directly via email to request a refund, especially if you were unintentionally charged or have not used the service.

What are Hugging Face Jobs and how are they priced?

Hugging Face Jobs allow you to run compute tasks on Hugging Face infrastructure. Billing is based on hardware usage (CPU and GPU options) and is computed by the minute, only when the Job is 'Starting' or 'Running'. Exposed ports are also billed at a flat hourly rate.

What kind of hardware is available for Hugging Face Spaces?

Hugging Face Spaces offer various on-demand hardware options, including CPU Basic (free), CPU Upgrade, ZeroGPU (free), and a range of Nvidia GPUs like T4, L4, L40S, A10G, and A100, with varying vCPU, memory, and VRAM configurations.

Use Cases
  • Machine learning engineers needing a collaborative platform
  • Researchers looking for pre-trained models and datasets
  • Developers deploying AI applications with scalable infrastructure
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