What Is Hugging Face? | Definition from TechTarget – TechTarget
Hugging Face is a machine learning (ML) and data science platform and community that helps users build, deploy and train machine learning models.
It provides the infrastructure to demo, run and deploy artificial intelligence (AI) in live applications. Users can also browse through models and data sets that other people have uploaded. Hugging Face is often called the GitHub of machine learning because it lets developers share and test their work openly.
Hugging Face is known for its Transformers Python library, which simplifies the process of downloading and training ML models. The library gives developers an efficient way to include one of the ML models hosted on Hugging Face in their workflow and create ML pipelines.
The platform is important because of its open source nature and deployment tools. It allows users to share resources, models and research and to reduce model training time, resource consumption and environmental impact of AI development.
Hugging Face Inc. is the American company that created the Hugging Face platform. The company was founded in New York City in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond and Thomas Wolf. The company originally developed a chatbot app by the same name for teenagers. The company switched its focus to being a machine learning platform after open sourcing the model behind the chatbot app.
In 2023, the company announced a partnership with Amazon Web Services to make Hugging Face products available to AWS customers for building custom applications. Google, Amazon and Nvidia are just a few of the companies that have invested in the startup as of this writing.
Hugging Face is an AI platform and supporting community. The community uses Hugging Face to do the following:
The Hugging Face Hub is where to find some of the main features of Hugging Face, including the following:
Hugging Face is free to sign up for as a community contributor. Users get a Git-based repository where they can store Models, Datasets and Spaces. After creating an account, users can do the following:
Hugging Face also offers a paid pro account that gives users access to more features, and an enterprise account at a slightly higher rate. The enterprise account adds enterprise-grade security and access control features, as well as dedicated customer support.
The open source, communal nature of Hugging Face provides several benefits:
There are also some considerations and risks to weigh against the benefits of Hugging Face, including the following:
Hugging Face reinforces a more collaborative approach to AI development in comparison with other contemporary AI startups, which develop an AI service and charge people to use it while keeping the inner workings of the technology a trade secret.
As more companies seek to develop their own AI models, Hugging Face will provide developers with the tools to do so. As the saying goes: In a gold rush, sell shovels. Many large companies already collaborate with Hugging Face to take advantage of its development platform.
Hugging Face aims to distribute AI access to many instead of restricting it to a few key players. Some employees at generative AI companies hold the opinion that open source AI will out-compete closed source AI providers such as OpenAI and Google. A leaked communication from a Google researcher in early 2023 expressed the researcher’s opinion that Google has “no moat” in the industry: “While we’ve been squabbling, a third faction has been quietly eating our lunch.”
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