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Post #2154 18
Hugging Face (Twitter)

RT @nvidia: Just released at #CES2026 - we're expanding the NVIDIA open model universe across industries to advance the development of real-world AI systems. Introducing new models, data, and tools for:

🗣️NVIDIA Nemotron for agentic AI
💪NVIDIA Cosmos for physical AI
🚙 NVIDIA Alpamayo for AVs
🤖 NVIDIA Isaac GR00T for robotics
🧬 NVIDIA Clara for biomedical

Get the latest updates here: nvda.ws/4jrX6S4
Post #2153 13
Hugging Face (Twitter)

RT @ClementDelangue: It's fun to see all the tall futuristic humanoid robots but it looks like Reachy Mini is the one taking the spotlight at CES. From a Jensen Keynote to managing a photobooth, it looks like it's everywhere!

And because it's the only AI robot that can be bought by all (we shipped 3,000 homes just before the end of the year), it has a real shot at becoming the foundation for AI robots in 2026, let's go! 🦾🦾🦾
Post #2148 18
Hugging Face (Twitter)

RT @Thom_Wolf: Reachy Mini starring in Jensen's CES keynote 🌟

really proud is was so prominently featured on stage and humbled that our product is getting so many AI builders excited and building

you don't have to make humanoids just because everyone else is talking about them – be contrarian - build what you think is the right thing to create now
Post #2147 16
Hugging Face (Twitter)

RT @NVIDIADRIVE: Curious how reasoning-based autonomous vehicles are built in practice?

See how NVIDIA Alpamayo brings together open models, datasets, and simulation in a full reasoning-based AV workflow:

🔹 Generate trajectory predictions with reasoning traces using Alpamayo 1, available on @huggingface
🔹 Train and evaluate models with Physical AI Open Datasets
🔹 Test end-to-end performance in AlpaSim, an open-source closed-loop simulator

Get started → nvda.ws/45z9PMP

#CES2026
Post #2145 18
Hugging Face (Twitter)

RT @NVIDIAAIDev: NVIDIA Cosmos Reason 2 is here. 🥳

An open, highly accurate reasoning vision language model for physical AI, featuring:

✅ Improved spatio-temporal understanding and timestamp precision
✅ Flexible deployment with 2B and 8B model sizes
✅ Long-context reasoning with up to 256K tokens
✅ Expanded visual perception across complex environments

We also have new Cosmos releases: Predict 2.5, Transfer 2.5, and the NVIDIA GR00T N1.6 robot foundation model.

📗Read our technical blog: nvda.ws/4swwC68
🤗 Download Cosmos Reason 2 on @HuggingFace: nvda.ws/3L4B6Qy
Post #2144 17
Hugging Face (Twitter)

RT @pranamanam: Introducing PeptiVerse 🚀, our open-source platform for therapeutic peptide property prediction. We support WT and modified SMILES inputs, and can predict solubility💧, permeability🔬, hemolysis🩸, non-fouling👯, half-life⏱️, tox ☠️, and binding affinity🔗 -- try it out!

🤗: https://huggingface.co/spaces/ChatterjeeLab/PeptiVerse
📜: https://www.biorxiv.org/content/10.64898/2025.12.31.697180v1

🧵👇
Post #2143 17
Hugging Face (Twitter)

RT @liquidai: Today, we release LFM2.5, our most capable family of tiny on-device foundation models.

It’s built to power reliable on-device agentic applications: higher quality, lower latency, and broader modality support in the ~1B parameter class.

> LFM2.5 builds on our LFM2 device-optimized hybrid architecture
> Pretraining scaled from 10T → 28T tokens
> Expanded reinforcement learning post-training
> Higher ceilings for instruction following

🧵
Post #2142 16
Hugging Face (Twitter)

RT @NVIDIARobotics: NVIDIA and @huggingface are integrating NVIDIA’s open Isaac technologies into the LeRobot library. 🤖

See how Isaac Lab-Arena, now available in @LeRobotHF Environment Hub, enables developers to evaluate VLA policies while creating robot environments that can be authored once and reused across the community.

Designed for scalable, open-source physical AI workflows. 🔗 nvda.ws/4qKy9Up
Post #2138 20
Hugging Face (Twitter)

RT @alvarobartt: 👾 `hf-mem` is all you need to estimate the required VRAM for inference of any model on @huggingface based on Safetensors metadata.

- Written in Python
- Lightweight, only depends on `httpx`
- Runs w/ @astral_sh `uvx` as `uvx hf-mem --model-id ...`
- Works with any Safetensors repository
- Output inspired by @usgraphics TR-100 Machine Report
Post #2137 20
Hugging Face (Twitter)

RT @remi_or_: Late Christmas gift for RL people 🎄

We are adding support for parallel decoding in transformers continuous batching!
You can now decode as many streams as you want from one prompt, which changes the game for long contexts 📜

but since a picture is worth 1024 words:
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