🕯️🔥[Candle](github.com/huggingface/...) is now much faster on macOS thanks to a contribution by @EricLBuehler, which brings major speed improvements to the Metal backend.🍎📈 Try it out by running some of our examples with the `--features metal` flag. #Candle #RustLang #macOS #Metal #HuggingFace

I just published part 2 of my article series about creating tensors from scratch in Rust. This one is about view operations. #tensors #machine-learning #ml #ai Take a look here: huggingface.co/blog/KeighBe...

I'm writing an article series about creating tensors from scratch in Rust. #tensors #machine-learning #ml #ai huggingface.co/blog/KeighBe...

Qwen 3 is now supported in Candle! Run the 3-4B model locally with: ``` cargo run --example qwen --release -- --model 3-4b --prompt 'The capital of France is ' ``` On macOS, enable Metal for faster inference: ``` --features metal ``` Clone the repo and test it out. github.com/huggingface/...

RIFTS Dataset: Solving Critical LLM Conversation Failures - LLMs 3x less likely to clarify than humans - 16x less likely to provide follow-up requests - Early failures predict later breakdowns - Includes preliminary intervention strategies huggingface.co/datasets/mic...

Google just released Gemma 3, an open, on-device LLM with vision capabilities and support for over 140 different languages. Models range from 1B-27B parameters. Zero-day support for multiple frameworks including transformers, MLX, llama.cpp, and more! 💼 🚀 Read more here: huggingface.co/blog/gemma3

Made some significant updates to the @hf.co semantic datasets search app. If you love falling into a wiki black hole, you might like this... huggingface.co/spaces/libra...

What to know about DeepSeek youtu.be/0eMzc-WnBfQ?... In which we attempt to figure out MoE, o1, scaling, tech reporting, modern semiconductors, microeconomics, and international geopolitics.

Over-Tokenized Transformer: Vocabulary is Generally Worth Scaling Hongzhi Huang, Defa Zhu, Banggu Wu, Yutao Zeng, Ya Wang, Qiyang Min, Xun Zhou tl;dr: increasing input vocabulary is always good, increasing output vocabularies is good for bigger models. arxiv.org/abs/2501.16975

It’s a green light for the Frugal AI Challenge! 🚀 For the next month, we invite all members of the AI community to participate in one of our 3 AI for Climate tasks, with the goal of developing a highly accurate model while consuming as little energy as possible ⚡

Christmas came early! 🎅🏻 Today marks the newest release of the HuggingChat 🤗 update with some really exciting capabilities! First up, automatic context injection! 1) Open a file in a supported app, summon HFChat, and it pre-populates the context window. No more copy-pasting. /cc @hf.co

Preliminary data shows the Apple Neural Engine uses ~94% less energy than the CPU and ~75% less than the GPU 🤯 On the On-Device team at Hugging Face, we've been profiling energy usage for CoreML models. Here’s some data I collected: