Dead-end developer ☠️ Building on the 🤗 @huggingface Hub
Estissac, France
Joined February 2009
- Tweets4.1K
- Following2.8K
- Followers915
- Likes4.1K
Bertrand Chevrier retweeted
We just crossed:
- 20M AI builders on @huggingface
- 300PB of models, datasets, agent traces, and RL environments hosted on the @huggingface hub (9PB added by users just last week)
Also October was our biggest month ever in terms of DAUs, MAUs and revenue.
Let's go open-source AI!
Bertrand Chevrier retweeted
We spent $2m so you don't have to.
And so you can learn how to train MoEs.
Mixture-of-Experts LLMs are what powers the AIs you use everyday, and few people in the world know how to train them at scale (a handful at each top AI lab).
This handbook distills everything we learned in meticulously crafted chapters and figures.
Disclaimer: it may take days to read.
We hope to see 1000x more people able to train their own frontier models all over the world! 🤗
Congrats @Nouamanetazi @lvwerra @Thom_Wolf
Bertrand Chevrier retweeted
Challenge accepted
llama.app
Bertrand Chevrier retweeted
Llama ❤️ @huggingface Hub 🤗
Get started with thousands of LLMs with a few clicks, running lightning-fast on your computer 🦙
Private, local, open-source 🙌🏻
And now everybody realizes how important the open-weight approach is 🤗
We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math.
It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training.
We call this Weight-Space Programming: frontier LLMs can now natively read/write neural network weights! 🧵
Blog: rikiyat.github.io/blog/weigh…
Readers added context they thought people might want to know
LLM was given weights explicitly as text in prompt and used code/forward passes (per authors' logs) to ablate Qwen looping direction, a known thinking-mode issue per model card. Primarily fixed repetition in that mode, not general 'natively' improving weights/math.
rikiyat.github.io/blog/weight-sp…
github.com/RikiyaT/lm_und…
huggingface.co/Qwen/Qwen3.5-0…
huggingface.co/RikiyaT/Qwen3.…
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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!
Took a minute to write a few words about security & safety as someone who lived through it all at OpenAI. I hope my thoughts help someone out there.
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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
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