Hugging Face operates a GitHub-like hub for AI code repositories, models and datasets alongside libraries for dataset processing and model evaluation, plus web apps to demo AI applications. Its paid offerings include AutoTrain for automated model training, an Inference API for hosted model serving, Infinity for faster in-production inference, and an enterprise hub supporting SaaS and on-prem deployments. The company also contributes to open-source models and initiatives such as BigScience and Bloom and has released models like StarCoder and SafeCoder. Hugging Face reports 10,000 customers, more than 50,000 organizations on the platform, and a model hub hosting over 1 million repositories; it has about 170 employees. Financially, the company was valued at $4.5 billion in its latest round and the valuation was reported to be more than 100 times its annualized revenue. Management says it plans to "double down" on research, enterprise and startup support and will recruit additional talent. Hugging Face hosts thousands of pre-trained machine-learning models, datasets, and developer-contributed repositories and positions itself as the “GitHub of machine learning.” Its Transformers library (on GitHub) has attracted significant attention, with 62,000 stars and 14,000 forks, and the site lets developers create, discover, and collaborate on models and apps. The company also offers hosted services, including an Inference API to use models via an API and an AutoTrain feature to train models. Ten thousand companies are using Hugging Face in some capacity, underscoring enterprise adoption. With the new funding, the company plans to continue expanding these developer- and enterprise-facing offerings rather than pivoting product strategy. Hugging Face maintains Transformers, an open-source NLP library that exposes popular models such as BERT, GPT, XLNet, T5 and DistilBERT. The Transformers GitHub repository has about 42,000 stars and 10,000 forks. Around 5,000 companies use Hugging Face in some capacity, including Microsoft (Bing) and Monzo; paying customers include Bloomberg and Typeform. The company recently launched paid offerings for prioritized support, private model management and a hosted inference API. Hugging Face reported being cash-flow positive in January and February 2021 and that roughly 90% of its prior $15 million round remains in the bank. It plans to triple headcount in New York and Paris and hire remote positions. Hugging Face began with a mobile chatbot app and has since released Transformers, an open-source library for natural language processing. Transformers has been downloaded more than one million times and its GitHub project has about 19,000 stars. Researchers at Google, Microsoft and Facebook have experimented with the library, and companies including Monzo and Microsoft Bing use it in production for tasks like classification, summarization, generation and conversational AI. The company plans to triple its headcount across New York and Paris with proceeds from the latest funding. The article frames Hugging Face’s core product as a widely adopted open-source NLP framework that underpins both research and commercial deployments. No revenue figures or other financial metrics are reported in the article. Hugging Face builds a chatbot app with a strong, personality-driven focus on emotions and entertainment for bored teenagers. The app is available in the App Store and on Kik, and the company is launching Hugging Face on Messenger to bring new users. It accepts text, photos, and emojis so the bot can interpret selfies and emotional cues. The service handles about 1 million messages per day and has processed over 100 million messages to date. The team has published AI research papers and plans to double its engineering staff in the coming months. The company recently raised a $4 million seed round to support product growth and hiring.

Total raised

$395M

Funding rounds

6

Latest round

Series D

Latest activity

Aug 2023