Hugging Face

Hugging Face (Twitter)

RT @mervenoyann: GLM-5 is out on @huggingface 🔥

> A40B/744B, trained on more tokens (28.5T)
> outperforms/on par with closed sota
> allows commercial use (MIT licensed) 💗

use with vLLM/SGLang locally or through HF Inference Providers thanks to @novita_labs and @Zai_org 📦

Hugging Face (Twitter)

RT @Zai_org: Introducing GLM-5: From Vibe Coding to Agentic Engineering

GLM-5 is built for complex systems engineering and long-horizon agentic tasks. Compared to GLM-4.5, it scales from 355B params (32B active) to 744B (40B active), with pre-training data growing from 23T to 28.5T tokens.

Try it now: chat.z.ai
Weights: huggingface.co/zai-org/GLM-5
Tech Blog: z.ai/blog/glm-5
OpenRouter (Previously Pony Alpha): openrouter.ai/z-ai/glm-5
Rolling out from Coding Plan Max users: z.ai/subscribe

Hugging Face (Twitter)

RT @AntLingAGI: One for all, and all for one 🧧
Introducing Ming-flash-omni-2.0: A specialist in every domain, unified as a capable generalist. A gift from Ling =)
- Unified Acoustic Synthesis: Speech, audio, and music combined for unbounded creativity;
- "Seeing" to "Knowing": Moving beyond input to true deep semantic understanding;
- Native Visual Fusion: Seamless generation, editing, and segmentation;

Hugging Face (Twitter)

RT @joinstationf: Europe is building. We’re leading. We're launching F/AI.

STATION F x @OpenAI, @Microsoft, @Meta, @MistralAI, @Google, @awscloud, @AnthropicAI, @AMD, @huggingface, @Lovable, @clay, @OVHcloud, @Snowflake, @Cloudflare, @Qualcomm, G42, @sequoia, @generalcatalyst, @lightspeedvp, @seedcamp, @kimaventures, @20vcFund, @motierventures, @DrysdaleVC

Hugging Face (Twitter)

RT @Xianbao_QIAN: Oh I need this model in my OpenClaw!

SoulX-Singer, a great zero-shot singing voice synthesis model has been released on @huggingface

Apache 2 license as well!

Check out the demo: https://huggingface.co/spaces/multimodalart/SoulX-Singer
And the model: https://huggingface.co/Soul-AILab/SoulX-Singer

Hugging Face (Twitter)

RT @MaziyarPanahi: 🚨 OpenMed just expanded the PII detection arsenal.

105 language-specific models for French, German, and Italian, now open source.

All Apache 2.0. All free. Forever.

European healthcare AI just got a lot more accessible. Supporting GDPR, HIPAA, and privacy compliance:
🇫🇷🇩🇪🇮🇹

Hugging Face (Twitter)

RT @UnslothAI: You can now train MoE models 12× faster with 35% less VRAM via our new Triton kernels (no accuracy loss).

Train gpt-oss locally on 12.8GB VRAM.

In collab with @HuggingFace, Unsloth trains DeepSeek, Qwen3, GLM faster.

Repo: github.com/unslothai/unsloth
Blog: https://unsloth.ai/docs/new/faster-moe

Hugging Face (Twitter)

RT @MistralAI: Introducing Mistral AI's biggest hackathon ever!
📅 Feb 28 - Mar 1
🌍 Paris | London | NY | SF | Tokyo | Singapore | Sydney & online
48 hours. The best hackers.
🤝 Partners: @wandb @nvidia @awscloud @HackIterate
🏆 $200K in prizes. Special awards from @elevenlabsio @huggingface @JUmp @whitecircle @supercell
Link in 🧵

Hugging Face (Twitter)

RT @lancedb: 1/6 OpenVid-1M in Lance format shows what’s possible when videos, metadata, embeddings, and indexes live in the same dataset.

~938K videos, inline blobs, prebuilt indexes — all queryable directly on the 🤗 @huggingface Hub. 🧵👇

Hugging Face (Twitter)

RT @xenovacom: After nearly a year of development, 🤗 Transformers.js v4 Preview is finally out on npm!

npm i @huggingface/transformers@next

Build WebGPU-accelerated AI applications that run everywhere: browsers, Node.js, Bun, Deno, Electron, and more.

See what's new in our blog post 👇

Hugging Face (Twitter)

RT @vanstriendaniel: Datasets and benchmarks drive AI progress, but finding papers that introduce new ones means digging through thousands of arXiv abstracts.

Updated the Dataset Papers on ArXiv app to surface them: 52K+ papers classified as introducing new datasets from 212K CS papers.

Semantic search, confidence filtering, updated weekly (using @huggingface Jobs!)

Powered by a fine-tuned ModernBERT classifier. Full dataset stored in @lancedb Lance format on the Hub, with vector embeddings stored with the dataset.

‌Hugging Face (Twitter)

Check out our changelog for more information huggingface.co/changelog

Hugging Face (Twitter)

We have been shipping 🛳️❤️

📦 Community Evals & Benchmark Datasets: Benchmark datasets host benchmark leaderboards, you can now contribute eval results by opening a PR to model repositories, all PRs are fed to benchmark datasets

📦 Chat with datasets: agents live in Data Studio, you can ask questions about datasets

📦 Select sections in datasets: Data Studio now has a spreadsheet-like UX, allowing quick selections

📦 MLX compatibility: Find hardware compatible for MLX models and quantized versions in model repositories

📦 You can now save blog drafts and access them from the editor 📖

📦 Datasets now support LanceDB format

📦 Model repositories show snippets for SGLang

‌Hugging Face (Twitter)

Read the blog: 📖

Hugging Face (Twitter)

We just shipped Community Evals and Benchmark repositories for decentralized evals 🤗

> Scores you and model authors report are on leaderboards 🙌🏻
> Benchmark datasets host live leaderboards of reported results 🚀
> You can open PRs to add scores, they live in model repositories.

Community Evals will expose scores currently distributed across model cards, papers, and benchmarks.
It won’t solve the differences in scores, but it is transparent!

Hugging Face (Twitter)

RT @hf_status: Hub website is back!
Thanks a lot for your patience 🤗

Hugging Face (Twitter)

RT @mervenoyann: agents are now running @huggingface dataset viewers 🤯

Hugging Face (Twitter)

RT @intern_lm: 🚀Introducing Intern-S1-Pro, an advanced 1T MoE open-source multimodal scientific reasoning model.

1⃣SOTA scientific reasoning, competitive with leading closed-source models across AI4Science tasks.
2⃣Top-tier performance on advanced reasoning benchmarks, strong general multimodal performance on various benchmarks.
3⃣1T-A22B MoE training efficiency with STE routing (dense gradient for router training) and grouped routing for stable convergence and balanced expert parallelism.
4⃣Fourier Position Encoding (FoPE) + upgraded time-series modeling for better physical signal representation; supports long, heterogeneous time-series (10^0–10^6 points).

😍Intern-S1-Pro is now supported by vLLM @vllm_project and SGLang @sgl_project @lmsysorg — more ecosystem integrations are on the way.

☺️Model：@huggingface
https://huggingface.co/internlm/Intern-S1-Pro
☺️GitHub:
https://github.com/InternLM/Intern-S1
☺️Try it now at:
chat.intern-ai.org.cn

Hugging Face (Twitter)

RT @Xianbao_QIAN: The new audio generation model from @acemusicAI and @StepFun_ai is mindblowing. Try it out on @huggingface :

Demo: https://huggingface.co/spaces/ACE-Step/Ace-Step-v1.5

Model: https://huggingface.co/ACE-Step/Ace-Step1.5 https://twitter.com/acemusicAI/status/2018731205546684678#m