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stop writing CUDA kernels yourself we have launched Kernel Hub: easy optimized kernels for all models on Hugging Face Hub 🔥 use them right away! it's where the community populates optimized kernels 🤝 keep reading 😏

Game changing feature shipped today on Hugging Face (IYKYK 🤣)

Ever wondered how models actually see an image? Been playing with some visualizations of patch extraction, token layouts, how they affect predictions too. Planning a short visual deep dive comparing how different models process images. Would love thoughts before I go on.

not bad at all, over a million requests on Hugging Face x @fal 🤗

🚀 SGLang now supports Hugging Face Transformers as a backend! Run any transformers-compatible model with fast, production-grade inference — no native support needed. Just plug and play 🥳 Blogpost: huggingface.co/blog/transform…

Super nice work with the SGLang team! 🫡

Let's fine-tune DeepSeek-R1 (distilled Llama) 100% locally:

My first project at Snowflake AI Research is complete! I present to you Arctic Long Sequence Training (ALST) Paper: arxiv.org/abs/2506.13996 Blog: snowflake.com/en/engineering… ALST is a set of modular, open-source techniques that enable training on sequences up to 15 million

Finally, a TTS model that sounds Indian 🇮🇳. Also commendable that they open-sourced it and made it available on Hugging Face. Congrats Maya Research

Sometimes I wish AI would be much better than now, and I work hard for it. Then I realize I would be jobless, miserable and sad...

"The great unbloating" of transformers continues. Over the past few weeks, 10+ PRs were merged, aiming to simplify code across the library. This brought in refactors for Attention, the Cache, a new linter. We're improving type hints everywhere, and are checking type checkers.

Evaluation was just made easier 💯 We merged a huge refacto of lighteval making easier to add: 🔄 Multiturn tasks 🖼️ Multimodal tasks 📝 Plus unified logs for thorough benchmark analysis Benchmarks guys, what evals would you like to see added ?

I’m so excited to announce Gemma 3n is here! 🎉 🔊Multimodal (text/audio/image/video) understanding 🤯Runs with as little as 2GB of RAM 🏆First model under 10B with lmarena.ai score of 1300+ Available now on Hugging Face, Kaggle, llama.cpp, ai.dev, and more

🚀Excited to announce that the ERNIE 4.5 series models are officially open-sourced today! 🙌ERNIE 4.5 models achieved state-of-the-art performance across multiple text and multimodal benchmarks, especially in instruction following, world knowledge memorization, visual

BOOOM! transformers now has a baked-in http server w/ OpenAI spec compatible API Launch it with `transformers serve` and connect your favorite apps. Here I'm running 👋 Jan with local transformers and hot-swappable models. There is preliminary tool call support as well!

I am actually quite baffled by this.... You add a model to transformers, even if you do this locally just before a release or anything, and you can already run it.... BTW x3 speedups coming for this 👀

Looks very strong! 💪

LET'S GO! Cursor using local 🤗 transformers models! You can now test ANY transformers-compatible LLM against your codebase. From hacking to production, it takes only a few minutes: anything `transformers` does, you can serve into your app 🔥 Here's a demo with Qwen3 4B: