Hugging Face

Hugging Face (Twitter) RT @liquidai: Meet the strongest 3B model on the market. LFM2-2.6B-Exp is an experimental checkpoint built on LFM2-2.6B using pure reinforcement learning. > Consistent improvements in instruction following, knowledge, and math benchmarks > Outperforms other 3B models in these domains > Its IFBench score surpasses DeepSeek R1-0528, a model 263x larger Download and play 👉https://huggingface.co/LiquidAI/LFM2-2.6B-Exp Happy holidays, The Liquid AI team🎄✨

Hugging Face (Twitter) RT @zRdianjiao: Been busy, still have many Pull Requests to submit. After Christmas, it will be a busy review process https://twitter.com/Zai_org/status/2003828175089098943#m

Hugging Face (Twitter) RT @dkundel: I was going to take a break from coding over the holidays...I guess now I have to ask Codex to tap in and help get my @huggingface Reachy Mini up and running 😄

Hugging Face (Twitter) RT @ehcalabres: 🎁 Last-minute gift from Santa! 🎅 FOMO over the Reachy Mini by @pollenrobotics & @huggingface? No hardware, no problem! Build and prototype your AI apps for free in the simulation. The only catch? You can’t pet him! 🤖 Just install the Python SDK & start playing!

Hugging Face (Twitter) RT @Zai_org: Trending #1 on @huggingface again! We’ll keep open-sourcing next year.

Hugging Face (Twitter) RT @NielsRogge: You might have seen the very cool video of @victormustar showing hf.co/chat calling the Z-Image-Turbo model by @Ali_TongyiLab via MCP How to do this? 1. Go to https://huggingface.co/spaces/Tongyi-MAI/Z-Image-Turbo 2. Click the little "MCP" icon at the top 3. Click "add to MCP tools" 4. Profit

Hugging Face (Twitter) RT @ClementDelangue: Happy Holidays, from our 🤖 family to yours!

Hugging Face (Twitter) RT @LeRobotHF: We’ve teamed up with @XSquareRobot to integrate WALL-OSS, a powerful new VLA foundation model into LeRobot!

Hugging Face (Twitter) RT @pa_balland: Something big is happening in robotics - and it’s hiding in plain sight. This post is not about dancing robots but in the data that powers them. Open robotics datasets have exploded this year, turning the field into a more scalable and collaborative ecosystem. In just two years, @huggingface datasets grew from 11k to over 600k - and robotics is by far the fastest-growing segment. We went from 1k robotics datasets in 2024 to 27k in 2025! For comparison, text generation, the second-largest category, has only around 5k datasets in 2025. That gap is massive. Open datasets are important because robotics lives and dies by real-world robot data - video, actions, sensors, failures. By making this data easy to upload, reuse, and benchmark, researchers, startups, and large players are now releasing real-robot datasets that would have stayed locked inside labs just a few years ago. Major contributors include @nvidia, LeRobot initiative, and... Перейти на оригинальный пост

Hugging Face (Twitter) RT @Zai_org: GLM-4.7 is here! GLM-4.7 surpasses GLM-4.6 with substantial improvements in coding, complex reasoning, and tool usage, setting new open-source SOTA standards. It also boosts performance in chat, creative writing, and role-play scenarios. Default Model for Coding Plan: z.ai/subscribe Try it now: chat.z.ai Weights: http://huggingface.co/zai-org/GLM-4.7 Tech Blog: z.ai/blog/glm-4.7

Hugging Face (Twitter) RT @OfficialLoganK: just ordered!

Hugging Face (Twitter) RT @mervenoyann: ah yes @huggingface the activewear company ™️