ML at Hugging Face 🤗

Joined May 2012
1,209 Photos and videos
Pinned Tweet
Had the honor to present diffusion transformers at CS25, Stanford. The place is truly magical. Slides: bit.ly/dit-cs25 Recording: youtu.be/vXtapCFctTI?si=dlcE… Thanks to @stevenyfeng for making it happen!
19
137
1,108
188,596
Sayak Paul retweeted
We want to work with kernel developers to help them publish their cool kernels on the @huggingface Hub via🤗 Kernels. This has several advantages: * A consistent build structure * Extreme ease of use * Standardized distribution * Reproducibility Reach out if interested 🤗
5
6
65
9,436
Sayak Paul retweeted
People replace their phones every ~4 yrs. This means there are hundreds of millions of old phones discarded each year that are still perfectly usable as computing devices. @Google in collabration with @UCSD is exploring how to turn these old phones into cloud-computing “phone clusters”. Putting phones back in service in this way can directly reduce the environmental footprint of computing by avoiding the need for further raw material extraction, and taking advantage of the embodied carbon already incurred from manufacturing these devices, and modern phones actually are already quite powerful computers. Read more in the blog below ⬇️
Today on the blog, we discuss a pathway for the second life of phones through the exploration of “phone cluster computing”, which can directly reduce the environmental footprint of computing by avoiding the need for further raw material extraction. More →goo.gle/4aJe5vO

ALT Animation of the construction of a server using smartphones.

132
480
4,906
522,041
Sayak Paul retweeted
Published my first kernel to go the last mile to optimize LTX-2.3 from @Lightricks! torch.compile cuDNN attn already gave a 1.42x boost. W/ the custom kernel added, I got 1.52x on a GB10 🔥 This was my systematic exploration of a simple agentic kernel dev workflow. More 👇
8
6
59
9,665
Published my first kernel to go the last mile to optimize LTX-2.3 from @Lightricks! torch.compile cuDNN attn already gave a 1.42x boost. W/ the custom kernel added, I got 1.52x on a GB10 🔥 This was my systematic exploration of a simple agentic kernel dev workflow. More 👇
8
6
59
9,665
When this kernel was patched in, it delivered the finale! Some visible and consistent gains _without_ any regression in the outputs.
1
1
355
It takes a special kind of commitment to provide this kind of direction to the readers. Part II of the profiling posts is up, diligently brought to you by @ariG23498. Check it out at hf [dot] co / blog / torch-mlp-fusion 🔥
4
1
19
1,311
I have to clear some stuff up. When I was contacted to be included in this article, "Agentic AI" didn't sound like the sole focus of it. This is what I was told: > We’re currently working on a listicle featuring some of the top developers and AI builders from India who are making an impact through open-source, AI, infrastructure, and agentic AI projects. I want to clarify that I am definitely not an Agentic Software Developer nor did I pioneer anything that's happening in the field. I thought they were reaching out to folks who had experience in the other stuff too (e.g., open-source) and not JUST agentic stuff. So, I respectfully request @Analyticsindiam to take my name down from the article.
4
39
4,210
Very indebted to @NVIDIAAI for the DGX Spark 🧨 Because of the beast that it is, I can test local kernel builds WHILE testing other things in parallel (like PEFT tests, compile tests, etc.). All of this without configuring a beefy cabinet or cooling system!
7
2
41
3,307
I like how `kernels` is getting into projects over time in an organic manner. If you work with custom kernels (be it the packaging or be it the consumption), consider giving the project a try 🤗 And let us know your feedback on the repo!
3
2
9
1,058
Coded or "Clauded"?🤪
2
11
1,182
Want to know if a kernel is compatible with your system configuration? We shipped `get_kernel_variants()` to make it easier! Query every kernel available on the Hub and know if it'd run on your machine 🫡
1
3
36
2,370