Dead-end developer ☠️, Front-end on the 🤗 @huggingface Hub Browser, Free Software, Vim, Svelte. https://xitter.cf/t.co/tY2n0xlc7D 🦅 🎸 apprentice & metalhead 🤘
Estissac, France
Joined February 2009
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Bertrand Chevrier retweeted
Fun and crazy napkin math: Meta, NVIDIA, Alibaba, DeepSeek, Moonshot, Mistral and ~30 other labs have shared close to $1B worth of training compute on the Hugging Face Hub
Free to download
End of 2023 it was under $40M
Wikipedia was written in volunteer hours. This AI age commons is written in GPU-hours and data
(it's a floor btw: about half comes from official compute numbers rest is educated guess and it still miss the ~900k community fine-tunes)
Space with data to explore: thomwolf-hub-dollars.static.…
Bertrand Chevrier retweeted
I asked claude to make a music video for our robot.
It took the job way too seriously.
The full movie (2:12): youtu.be/HfVUu1KMi-A
@pollenrobotics x @huggingface
Bertrand Chevrier retweeted
Mistral 4 on Hugging Face soon 🤯
huggingface.co/mistralai/Mis…
Bertrand Chevrier retweeted
I'm giving away $1,000 of HF credits 🤗
$10 x 100 people, I want you to experience this:
> having your agent launch hundreds of HF Jobs
> run ~33M tokens of DeepSeek V4.1 Flash
> deploy your own dedicated Qwen3.8 27B endpoint
> Agents + Blender on a GPU because it's 🔥
Just reply with your HF username 👇
Hugging Face Jobs usage is stonking 📈
All thanks to agents: you just need the hf CLI installed and you have access to an insane amount of hardware.
Asked mine to test hundreds of code snippets from Hub model pages: it launched 322 Jobs in 90 minutes, up to 25 at once, CPU to A100 (diffusers, transformers, sklearn, MLX, Keras...)
Total bill: ~$4 🤯
I know what you did last summer 🪝
Great article @joedaroo!
Bertrand Chevrier retweeted
One last thing from me about the HF<>OpenAI "rogue agent" incident.
From what we now know it seems @huggingface was the first organization to simultaneously satisfy the following factors:
1/ awareness of the attack
2/ awareness that the attack was Agent-based
3/ ability to remediate the attack
4/ willingness to publicly disclose it
A few other platforms or systems missed one or more of those points in the earlier months.
As usual, both awareness and transparency make everyone safer in the long run 🙏
I've been working with herdr 🐏 for a few days.
It's pretty nice
herdr.dev
Many companies will follow...
Latham & Watkins buys Nvidia servers to set up in-house AI systems ft.trib.al/0CRKbBl
Bertrand Chevrier retweeted
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! 🤗🤗🤗
Bertrand Chevrier retweeted
terminal-bench by the @harborframework folks is arguably the most important benchmark of the last year, referenced and used by every major model builder, and currently being led by the usual suspects on the @huggingface open leaderboard 👀
🏆 Winners
🥇 @Kimi_Moonshot Kimi k3
🥈 @deepseek_ai v4 Pro
🥉 @Alibaba_Qwen Max
Honorable Mention to @Alibaba_Qwen's 3.8 27B of course, being the best model under 128B params...
Composed of 89 tasks, all super high quality: from fixing an OCaml GC bug to recovering a corrupted SQLite DB. It's helped steer the field toward efficient, local agents.
If you don't know what local model to use checkout the terminal-bench leaderboard.. 👇
