So happy to finally share the news in person It’s been a wild ride for Hugging Face. We certainly did not anticipate, back in 2016, as a tiny team of scrappy underdogs, that the field would grow so much or that the impact we could have on it would become so massive. I remember @julien_c joking that « code will be a subset of ML » several years ago. The joke turned out to be true, and the pleasure we’ve had being part of this transformation and pushing an alternative vision of AI as open, collaborative and distributed has been and still is immense. We’ve always built things seriously while not taking ourselves too seriously at Hugging Face (special congrats if you find the Hugging Face and Nvidia references hidden in our $12,930,300,000 acquisition price), and we plan to keep doing what we've been doing, just at a much bigger scale, backed by the resources, expertise and drive of Nvidia. And to be clear, nothing changes for our users today. No company in the world has been a more natural fit with our mission than Nvidia. From open-source, open-weights and open science to robotics and AI for science, they have been close partners across everything we care about. So when Jensen offered @ClementDelangue the opportunity to double down on building the Hub as an open, independent and compute agnostic platform, we decided the time was right to start the next 10 years of our journey together. We’re at an important inflection point for open-source AI, where scale and compute are becoming increasingly essential. We’re excited to have the resources to push further, build more ambitiously, and bring you even more projects and news in the coming months.

Super happy to share our intention to join forces with NVIDIA in a $12,930,300,000 acquisition 💛💚 10 years after starting Hugging Face, open-source AI is at an inflection point. Thanks to the community, we’ve shown that it can be a complement, and even an alternative, to closed-source APIs. But for it to happen at larger scale, it needs more compute, more support, more collaboration and more visibility. That’s why we went to talk to Jensen, who offered to do exactly that with us. In addition to doubling down on NVIDIA’s massive contributions to open-source AI (I called them the “King of American open-source AI” earlier this year), they’ve committed to strongly supporting Hugging Face and our mission while keeping the platform open, independent and compute agnostic. The founders and the team are all staying to keep pushing this mission forward. Together, we think we can make open source the default way to build AI, with the goal of empowering 100 million AI builders to own their intelligence rather than rent it. Excited about the next 10 years! 🤗🤗🤗

Exciting day for NVIDIA and @huggingface. Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty. They allow every developer, startup, university, industry and country to build with, customize and benefit from AI. Thank you @ClementDelangue for coming to me. NVIDIA is going to be a great home for Hugging Face, its community and the future of open models. 🤗

Robots don't have to be scary! Microduck discovers Reachy Mini. Give me your best scenario for these two and I'll see what I can do. Don't push me too hard though, or I might end up making a whole movie.

The only tutorial you should attend at #ECCV26# (kidding 😂). But I am incredibly psyched to be doing this with the best bunch out there. I strongly feel this is a timely tutorial! We will present general approaches alongside our learnings from (post)-training impactful models like Flux2/3. Tutorial website: Save your calendars!

Excited to share that I joined @huggingface🤗 as a ML Advocate Engineer in Robotics ! Will work on showcasing what LeRobot can do on various hardware, starting with @menloresearch Asimov robot, stay tuned ! 🤖

Hugging Face is (also) the best place to write about AI. > Your articles are now automatically linked from your model pages, so anyone looking at the model finds what you wrote about it. > We shipped an improved UX to make writing, drafting and publishing better. > We made it great to use as a team: add coauthors to work together and have everyone credited on the post. Get HF Pro at $9/month or subscribe your org to Team or Enterprise to get started.

Even the choir singer jobs aren't safe from robots 😂😂😂 Kidding aside, this might be one of the most beautiful things I've seen from robots in a while. Each microduck has its own audio identity, tied to that individual robot that it keeps for life so that makes it even more poetic!

For folks wondering what Sliding Window Attention is, there's a method for it on Papers with Code Sliding Window Attention (SWA): A local attention pattern that restricts each token to attending only within a fixed-size neighborhood instead of the full sequence. This reduces attention and KV-cache memory for long-context models, while periodic global-attention layers can preserve broader context. Find it here:

Introducing TimesFM-3, a state-of-the-art time series foundation model that enables accurate multivariate time series forecasting in a single forward pass, significantly outperforming other forecasting models across major benchmarks. More on the blog →