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Clément Delangue

Co-Founder & CEO, Hugging Face

  • Open-Source AI
  • Founder
  • Community
Clément Delangue, red-ink portrait in the thehype style

Editorial bio

Clément Delangue is a French entrepreneur from La Bassée who started selling on eBay as a teenager and took online computer-science courses at Stanford alongside his studies at ESCP Business School. Before Hugging Face he worked at Moodstocks, a computer-vision ML startup later acquired by Google, and at Mention. In 2016 he co-founded Hugging Face with Julien Chaumond and Thomas Wolf, originally as a chatbot for teenagers; the pivot became the single most important community infrastructure in open-source AI.

The Hub, the Transformers library, and a growing stack of open models, evaluations and robotics tooling now sit under that bet. The company raised $235M at a $4.5B valuation, and Bloomberg's Billionaires Index has estimated his personal net worth around $1.8B. His argument, consistent across keynotes and X: the long-term equilibrium is not one closed frontier lab winning – it's thousands of specialised open models serving specific use-cases.

Worth following if you want the open-source AI argument from the CEO of the company that has already made it true at scale.

Key facts

based in
Miami / New York / Paris area
current
Co-Founder & CEO, Hugging Face
prior
Moodstocks (acquired by Google, 2016) · Mention (product/CMO) · teenage eBay seller & intern
education
ESCP Business School · online CS courses, Stanford
funding
$235M Series D at $4.5B valuation · personal net worth ≈ $1.8B (Bloomberg Billionaires Index)
focus
Open-source AI · model hub · open LLMs · robotics · community

Featured work

  1. company

    Hugging Face (Co-Founder & CEO, 2016–)

    The open-source AI hub; millions of models and datasets hosted.

  2. open source

    Transformers library

    The de facto open-source library for working with modern language models.

  3. funding

    $235M Series D at $4.5B valuation

    Among the largest open-source AI rounds on record.

  4. speaking

    Keynote positions on open vs. closed AI

    Shaping the policy conversation on open-source AI.

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