Hugging Face has raised a $40 million Series B funding round — Addition is leading the round. The company has been building an open source library for natural language processing (NLP) technologies. You can find the Transformers library on GitHub — it has 42,000 stars and 10,000 forks.
Existing investors Lux Capital, A.Capital and Betaworks also participated in today’s funding round. Other investors include Dev Ittycheria, Olivier Pomel, Alex Wang, Aghi Marietti, Florian Douetteau, Richard Socher, Paul St. John, Kevin Durant and Rich Kleiman.
With Transformers, you can leverage popular NLP models, such as BERT, GPT, XLNet, T5 or DistilBERT and use those models to manipulate text in one way or another. For instance, you can classify text, extract information, automatically answer questions, summarize text, generate text, etc.
There are many different use cases for NLP. A popular one has been support chatbot. For instance, challenger bank Monzo has been using Hugging Face behind the scenes to answer questions from its customers. Overall, around 5,000 companies are using Hugging Face in one way or another, including Microsoft with its search engine Bing.
When it comes to business model, the startup has recently launched a way to get prioritized support, manage private models and host the inference API for you. Clients include Bloomberg, Typeform and Grammarly.
With the new funding round, the company plans to triple its headcount in New York and Paris — there will be remote positions too. Interestingly, the company is also sharing some details about its bank account.
Hugging Face has been cash-flow positive in January and February 2021. The company raised a $15 million round a little over a year ago — 90% of the previous round is still available on the bank account. And the company’s valuation saw a fivefold increase. This shouldn’t come as a surprise as you can negotiate better terms if you don’t actually need to raise.
And it looks like Hugging Face is on the right path as the company is hosting a vibrant community of NLP developers. You can browse models and datasets, take advantage of them and contribute as Hugging Face is becoming the central brick of NLP enthusiasts.
