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What is Hugging Face? The ML Platform For Building AI-Powered Apps

Profile Picture of Nicolas Azevedo
Nicolas Azevedo
Data Scientist and Machine Learning Engineer
A developer sitting next to the Hugging Face logo

Natural Language Processing (NLP) is a key component in powering human-computer interactions. As consumers, we’re using and adopting more NLP-powered solutions everyday: from chatbots to voice search to translations, NLP is what powers computers to understand, interpret, and respond to human language. These tools have become so commonplace it can be easy to forget that building them is extremely complex. That’s where libraries like Hugging Face come in.

Table Of Contents

Hugging Face stands out as a transformative toolkit in the NLP ecosystem. In this article, we’ll dive into what sets Hugging Face apart, exploring its core features, the diverse tasks it supports, the vibrant community behind it, and a practical example showcasing its user-friendly interface. Ready to explore the capabilities of Hugging Face? Let’s get started!

What is Hugging Face 🤗?

Hugging Face is an open-source machine learning tool that was initially developed to focus on NLP tasks. The original vision for the product was a unique one, too: Hugging face was built as an “AI BFF” chatbot for teenagers, providing emotional support and entertainment. 

An animated character on a background with a grid of the hugging face logo

Since its origins in 2016, Hugging face has expanded to include areas like computer vision, speech recognition, and even reinforcement learning (the process by which models are trained to make the most optimal decisions). Today, it’s a powerful platform where ML practitioners share and exchange their work (and has a valuation of $4.5 billion!) This collaborative environment facilitates the work of developers dealing with language data, making the development process simpler, faster, and more accessible for all.

A screenshot of Hugging Face's home page with its key value proposition

It’s easiest to understand the power of Hugging Face with an example.

Example: Using Hugging Face in an E-Commerce Business

Originally published on Jun 20, 2024Last updated on Jul 3, 2024
Key Takeaways

What is Hugging Face used for?

Hugging Face is a powerful platform where ML practitioners share and exchange their work. The tool offers curated data sets, pre-trained ML models, and demo AI-powered apps that can all be accessed through its web-based platform.

Why is Hugging Face so popular?

Today, it’s a powerful and popular platform where ML practitioners share and exchange their work (and has a valuation of $4.5 billion!) This collaborative environment facilitates the work of developers dealing with language data, making the development process simpler, faster, and more accessible for all.

Hugging Face is popular mainly because of the “Hugging Face hub,” which provides AI/ML researchers with access to thousands of curated datasets, machine learning models, and AI-powered demo apps. This collaborative platform enables researchers, developers, and enthusiasts to explore and experiment with a diverse range of ML models, accelerating innovation and knowledge sharing in the field.

Is Hugging Face free or paid?

Hugging Face offers various services and tools, some of them are free while others are paid. Here's a general overview. You can access unlimited models, datasets, and spaces; create unlimited orgs and private repos; and access the latest machine learning tools for free. Suppose you want to become a premium user. In that case, you can get early access to upcoming features, use the inference API at a higher rate, and in general the price becomes higher when it comes to companies; for companies, the features include priority support, custom solutions, deployment of the Inference API in the infrastructure of your preference, SSO and SAML support, and some other features.

What exactly does Hugging Face do?

There are three key features Hugging Face offers that simplify the process of working with ML data: Datasets, Models, and Spaces. Each of them are hosted on the Hugging Face Hub as Git repositories. This centralized hub ensures easy access and seamless integration into your workflow, allowing you to focus on building innovative ML solutions without the hassle of managing multiple platforms. 

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