New interactive viz from AI World showing OpenAI's new open model gpt-oss-120b breaking into the top 50 most liked models of all time on the Hub in under a day! ☄️☄️☄️
This is what Hugging Face is all about. We want everyone, hobbyists, researchers and industry alike, to be able to contribute to AI because everyone is affected by it. Kudos to HF's @irenesolaiman for spreading the word!🔥🤗
ZML just released a technical preview of their new Inference Engine: LLMD.
- Just 2.4GB container, which means fast startup times and efficient autoscaling - Cross-Platform GPU Support: works on both NVIDIA and AMD GPUs. - written in Zig
I just tried it out and deployed it on Hugging Face Inference Endpoints and wrote a quick guide 👇 You can try it in like 5 minutes!
We just released native support for @SGLang and @vllm-project in Inference Endpoints 🔥
Inference Endpoints is becoming the central place where you deploy high performance Inference Engines.
And that provides the managed infra for it. Instead of spending weeks configuring infrastructure, managing servers, and debugging deployment issues, you can focus on what matters most: your AI model and your users 🙌
With Sheets, try a new way to create structured content with the help of AI!
No installs. No login. Just open a link and 🤩
This app lets you create a dataset by importing a file or starting from a prompt.
What’s different about SHEETS? 🔎 Web search integration to ground answers in real-world data 📚 In-context learning from validated sources 🔗 Transparent sourcing — every result is linked 🧩 Runs on multiple open-source models
Fight hallucinations and start creating content you can rely on.
Inspired by Hugging Face's official MCP server, I've developed a complementary tool that exposes my semantic search API to enhance discovery across the HF platform.
Key capabilities:
- AI-powered semantic search for models and datasets - Parameter count analysis via safetensors metadata - Trending content discovery - Find similar models/datasets functionality - 11 tools total for enhanced ecosystem navigation
The semantic search goes beyond simple keyword matching, understanding context and relationships between different models and datasets.
Example query: "Find around 10 reasoning Hugging Face datasets published in 2025 focusing on topics other than maths and science. Show a link and a short summary for each dataset." (results in video!)
It's just become easier to share your apps on the biggest AI app store (aka HF spaces) for unlimited storage, more visibility and community interactions.
Just pick a React, Svelte, or Vue template when you create your space or add app_build_command: npm run build in your README's YAML and app_file: build/index.html in your README's YAML block.
Playing with Veo3 this morning. Share your prompt if you want me to create videos for you (bonus point if they funnily reference HF/open-source). These videos are "a cat on the moon rapping "I love Hugging Face""!
Yesterday, we dropped a new conversational viewer for datasets on the hub! 💬
Actually being able to view and inspect your data is extremely important. This is a big step in making data more accessible and actionable for everyone.
What are you using to evaluate models or AI systems? So far we're building lighteval & leaderboards on the hub but still feels early & a lot more to build. What would be useful to you?
