Hugging Face (Twitter)

RT @antoine_chaffin: Today is a big day
Today is Silksong day
But most importantly, today is the day I finally got HF socks!!!

Hugging Face (Twitter)

RT @maximelabonne: Liquid AI Japan cooked with this 350M param model on par with GPT-4o for English ↔ Japanese translation

That's a really nice example of fine-tuning done right 👌

Hugging Face (Twitter)

RT @mirkokiefer: My 2.5-year-old son controlling a robotic arm for the first time — and he genuinely picked it up faster than I did. He absolutely loves robots. The next generation will take over faster than we can blink.

That’s the @LeRobotHF so101, by the way.

Hugging Face (Twitter)

RT @LeRobotHF: 🚀 Big news: we just added Reachy 2 to LeRobot!

Huge thanks to our friends at @pollenrobotics 💛🤗
Reachy 2 is also available in simulation, so you can try it out right away.
🎥 Check out the teleop & autonomous demo below!

Hugging Face (Twitter)

RT @QuixiAI: Cannot wait to try the new Kimi K2! @Kimi_Moonshot

Hugging Face (Twitter)

RT @Laz4rz: Brand new, fresh out of a French printer

Hugging Face (Twitter)

RT @_fracapuano: “It’s a good dog, @ClementDelangue” vibes

Hugging Face (Twitter)

RT @fffiloni: Quietly landed on the hub
you can try ROSE on @huggingface 🤗
—> https://huggingface.co/spaces/Kunbyte/ROSE https://twitter.com/Almorgand/status/1962846321372471755#m

Hugging Face (Twitter)

RT @Thom_Wolf: This is huge

Continuing our foundational work to enable anyone to train state of the art AI model, we’re thrilled to release « FinePDFs »

3T tokens of textual data that until now was locked away in PDFs, arguably some of the highest quality publicly available data out there.

We gathered FinePDF to create the largest permissively licensed corpus sourced exclusively from PDFs.

Amazingly challenging infra and processing work, h/t to the fineweb team https://twitter.com/HKydlicek/status/1964584936524124645#m

Hugging Face (Twitter)

RT @HKydlicek: We are releasing 📄 FinePDFs:
the largest PDF dataset spanning over half a billion documents!

- Long context: Documents are 2x longer than web text
- 3T tokens from high-demand domains like legal and science.
- Heavily improves over SoTA when mixed with FW-EDU&DCLM web copora.

Hugging Face (Twitter)

RT @gpj: Released a new synthetic dataset: 1.5k [human] → 10k [synthetic] children’s stories.

Pipeline generated by @Kilo_Code and model switching from @poe_platform API 🙏🤗

https://huggingface.co/datasets/garethpaul/children-stories-dataset

Hugging Face (Twitter)

RT @maximelabonne: Pheww, another banger dataset from @huggingface!

> 3T tokens, 475M PDFs, 1733 languages

> Close to Nemotron-CC v2 and FineWeb-Edu+DCLM on its own (‼️)

> Greatly boosts perf when combined, likely because it provides high diversity that complements the other datasets well

Hugging Face (Twitter)

RT @TrackioApp: Trackio represents @huggingface's effort to democratize experiment tracking for the community:

> absolutely free,
> open-source,
> local-first
> drop-in alternative to commercial solutions

Hugging Face (Twitter)

RT @OfirPress: 3 out of the top 6 most downloaded datasets on @huggingface are SWE-bench related.

Thanks!!! ♥️

Hugging Face (Twitter)

RT @Thom_Wolf: wow, total BoM cost $660, folks

open-source community >> closed source hyped robots

Hugging Face (Twitter)

RT @LeRobotHF: Almost 10,000 followers here! Let's build the biggest and most active community of Robotics AI builders thanks to open-source!

Hugging Face (Twitter)

RT @Thom_Wolf: 3 trillions tokens finely distilled from more than a petabyte of PDF files

We’ve just released FinePDF, the latest addition to the Fineweb datasets

Hugging Face (Twitter)

RT @cgeorgiaw: 🚨 Big news in ML for biotech 🚨

Today, we're launching the Antibody Developability Prediction Competition with @Ginkgo + @huggingface!

💧 Hydrophobicity
🎯 Polyreactivity
🧲 Self-association
🔥 Thermostability
🧪 Titer

🏆 Up to $60k in prizes
📅 Submit by Nov 1, 2025

‌Hugging Face (Twitter)

RT @charlesbben: Recently finished writing a new blogpost about @PyTorch compilation in ZeroGPU Spaces.

Worth reading if you're interested in learning about :

- PyTorch ahead-of-time compilation
- ZeroGPU internals

https://huggingface.co/blog/zerogpu-aoti