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Fresh off a $100 million funding round, Hugging Face, which provides hosted AI services and a community-driven portal for AI tools and data sets, today announced a new product in collaboration with Microsoft. Called Hugging Face Endpoints on Azure, Hugging Face co-founder and CEO Clément Delangue described it a way to turn Hugging Face-developed AI models into “scalable production solutions.”

“The mission of Hugging Face is to democratize good machine learning,” Delangue said in a press release. “We’re striving to help every developer and organization build high-quality, machine learning-powered applications that have a positive impact on society and businesses. With Hugging Face Endpoints, we’ve made it simpler than ever to deploy state-of-the-art models, and we can’t wait to see what Azure customers will build with them.”

The demand for AI remains high. According to a recent McKinsey survey, nearly two-thirds of companies plan to increase their investments in AI over the next two years. But implementing AI from scratch can be challenging. Moreover, many companies have strict performance, security, compliance, and privacy requirements that require hosting models on tightly-controlled infrastructure.

Hugging Face Endpoints is Hugging Face’s solution to the problem.

Available through Azure Machine Learning Services, Hugging Face Endpoints allows customers to tap Hugging Face models with a few clicks or lines of Microsoft Azure SDK code. After selecting a model and a task type, customers can deploy the model wherever they choose on internal infrastructure, whether for an app, website, or backend service. 

Hugging Face’s models focus on text analysis — specifically tasks like summarizing and generating text, extracting information, and automatically answering questions. They’re largely based on the Transformer, the same model architecture underpinning OpenAI’s GPT-3 and countless other powerful AI systems.

Hugging Face Endpoints is launching in beta today — already, it’s being used by Standard Bank, a large South African bank and financial services group. And Microsoft Azure AI CVP Eric Boyd hints that it’s only the beginning of Hugging Face’s work with Microsoft. 

“Our vision with Azure AI is to build machine learning solutions that help our customers solve complex problems in the simplest, most scalable, and most secure way,” Boyd said in a press release. “We are pleased to support the launch of Hugging Face Endpoints, backed by Azure Machine Learning, as the first step of our collaboration with Hugging Face, and a proof point to our shared commitment to helping developers more quickly and easily deploy thousands of custom or pretrained transformer models.”