Hugging Face

Discover models and datasets, run demos and publish ML applications.

modelsdatasets
Websitehuggingface.co
CategoryAI & machine learning
PricingFreemium
Card requiredNo
← ← Back to directoryGo to Hugging Face ↗ ↗

ABOUT

What is Hugging Face?

Hugging Face is the central hub for open-source machine learning. It hosts hundreds of thousands of models and datasets and provides Spaces , lightweight hosted environments for running ML demos built with Gradio or Streamlit. The Inference API lets you call hosted models directly without any infrastructure setup, while the Transformers library is the industry standard for loading and running models locally.

BEFORE YOU SIGN UP

What you should know

✓
Largest open model repositoryHundreds of thousands of models across text, image, audio and multimodal tasks. The de-facto standard for discovering and sharing open weights.
✓
Spaces for instant demosDeploy a Gradio or Streamlit app in minutes. Ideal for sharing proofs of concept or giving clients interactive access to a model without building a full application.
△
Model quality varies widelyAnyone can publish a model. The number of downloads and the recency of the model card are the most reliable quality signals on the free tier.
✕
Free compute is intentionally smallCPU Basic and ZeroGPU Spaces can be used for free, while persistent or dedicated accelerator hardware is billed. Free users also receive only $0.10/month of Inference Providers credits.

COMMUNITY

From the forums

Hugging Face has near-universal recognition in the ML community. r/MachineLearning, r/LocalLLaMA and the broader AI developer community treat it as the default repository for open models. The main friction points are the free-tier Spaces running on slow shared CPU (leading to timeouts on larger models), inference API rate limits and the occasional model removal when authors delete their repositories.

— Community sentiment

💬Discuss on Reddit ↗

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ABOUT US

Honest, independent, no fluff.

No paid placements. Just a clear look at what this does, what it costs, and what to know before you commit.

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FAQ

Questions, answered.

What is the difference between the Inference API and running a model locally?＋

The Inference API calls a model hosted on Hugging Face servers , no GPU required on your end, but subject to rate limits and supported model availability. Running locally via Transformers or llama.cpp gives you full control but requires appropriate hardware.

Can I keep my model private on the free tier?＋

Yes. Private models and datasets are supported on the free tier, but private Spaces (for demos) require a paid Pro account.