๐ฏ Perplexity drops their FIRST open-weight model on Hugging Face: A decensored DeepSeek-R1 with full reasoning capabilities. Tested on 1000+ examples for unbiased responses.
Six months after joining Hugging Face the Xet team is kicking off the first migrations from LFS to our storage for a number of repositories on the Hub.
More on the nitty gritty details behind the migration soon, but here are the big takeaways:
๐ค We've successfully completed the first migrations from LFS -> Xet to test the infrastructure and prepare for a wider release
โ No action on your part needed - you can work with a Xet-backed repo like any other repo on the Hub (for now - major improvements on their way!)
๐ Keep an eye out for the Xet logo to see if a repo you know is on our infra! See the screenshots below to spot the difference ๐
โฉ โฉ โฉ Blazing uploads and downloads coming soon. Wโre gearing up for a full integration with the Hub's Python library that will make building on the Hub faster than ever - special thanks to @celinah and @Wauplin for their assistance.
๐ Want Early Access? If youโre curious and want to test it out the bleeding edge that will power the development experience on the Hub, weโd love to partner with you. Let me know!
Its own self-description? "A model for generating concise summaries of model & dataset cards from the Hugging Face Hub"
The goal? Make it easier to find the right models and datasets for your specific needs. It's already powering a semantic search for datasets Space.
It's still a WIP but thanks to @loubnabnl , @anton-l , @eliebak et al, for cooking such a nice base model for fine-tuning small, efficient models for specific domains and tasks. ๐
"๐ฎ๐ฌ๐ฎ๐ฑ ๐๐ถ๐น๐น ๐ฏ๐ฒ ๐๐ต๐ฒ ๐๐ฒ๐ฎ๐ฟ ๐ผ๐ณ ๐๐ ๐ฎ๐ด๐ฒ๐ป๐๐": this statement has often been made, here are numbers to support it.
I've plotted the progress of AI agents on GAIA test set, and it seems they're headed to catch up with the human baseline in early 2026.
And that progress is still driven mostly by the improvement of base LLMs: progress would be even faster with fine-tuned agentic models.
Toward the end of last year, the Xet team provided an inside look into the foundations of how we plan to enable rapid experimentation and iteration for the AI builders on the Hub: https://huggingface.co/blog/from-files-to-chunks
But it turns out chunks aren't all you need!
Our goal is to bring: ๐ Faster uploads โฌ Speedy downloads ๐ช All without sacrificing your workflow
To do that, we need the infrastructure and system and design to back it up. As we prepare to roll out the first Xet-backed repositories on the Hub, we wrote up a post explaining the nitty gritty details of the decisions that bring this to life https://huggingface.co/blog/from-chunks-to-blocks
Complete with an interactive visualization that shows the power of deduplication in action - taking a 191GB repo to ~97GB and shaving a few hours off upload speeds.
The darker each block in the heatmap, the more we dedupe, the less we have to transfer. Clicking on a file's blocks shows all other files that share blocks.
Multimodal ๐ฌ - We have released SmolVLM -- tiniest VLMs that come in 256M and 500M, with it's retrieval models ColSmol for multimodal RAG ๐ - UI-TARS are new models by ByteDance to unlock agentic GUI control ๐คฏ in 2B, 7B and 72B - Alibaba DAMO lab released VideoLlama3, new video LMs that come in 2B and 7B - MiniMaxAI released Minimax-VL-01, where decoder is based on MiniMax-Text-01 456B MoE model with long context - Dataset: Yale released a new benchmark called MMVU - Dataset: CAIS released Humanity's Last Exam (HLE) a new challenging MM benchmark
LLMs ๐ - DeepSeek-R1 & DeepSeek-R1-Zero: gigantic 660B reasoning models by DeepSeek, and six distilled dense models, on par with o1 with MIT license! ๐คฏ - Qwen2.5-Math-PRM: new math models by Qwen in 7B and 72B - NVIDIA released AceMath and AceInstruct, new family of models and their datasets (SFT and reward ones too!)
Audio ๐ฃ๏ธ - Llasa is a new speech synthesis model based on Llama that comes in 1B,3B, and 8B - TangoFlux is a new audio generation model trained from scratch and aligned with CRPO
Image/Video/3D Generation โฏ๏ธ - Flex.1-alpha is a new 8B pre-trained diffusion model by ostris similar to Flux - tencent released Hunyuan3D-2, new 3D asset generation from images
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post with ๐คโค๏ธ๐ฅ2 months ago
After some heated discussion ๐ฅ, we clarify our intent re. storage limits on the Hub
TL;DR: - public storage is free, and (unless blatant abuse) unlimited. We do ask that you consider upgrading to PRO and/or Enterprise Hub if possible - private storage is paid above a significant free tier (1TB if you have a paid account, 100GB otherwise)
We optimize our infrastructure continuously to scale our storage for the coming years of growth in Machine learning, to the benefit of the community ๐ฅ
๐ Announcing Global-MMLU: an improved MMLU Open dataset with evaluation coverage across 42 languages, built with Argilla and the Hugging Face community.
Global-MMLU is the result of months of work with the goal of advancing Multilingual LLM evaluation. It's been an amazing open science effort with collaborators from Cohere For AI, Mila - Quebec Artificial Intelligence Institute, EPFL, Massachusetts Institute of Technology, AI Singapore, National University of Singapore, KAIST, Instituto Superior Tรฉcnico, Carnegie Mellon University, CONICET, and University of Buenos Aires.
๐ท๏ธ +200 contributors used Argilla MMLU questions where regional, dialect, or cultural knowledge was required to answer correctly. 85% of the questions required Western-centric knowledge!
Thanks to this annotation process, the open dataset contains two subsets:
1. ๐ฝ Culturally Agnostic: no specific regional, cultural knowledge is required. 2. โ๏ธ Culturally Sensitive: requires dialect, cultural knowledge or geographic knowledge to answer correctly.
Moreover, we provide high quality translations of 25 out of 42 languages, thanks again to the community and professional annotators leveraging Argilla on the Hub.
I hope this will ensure a better understanding of the limitations and challenges for making open AI useful for many languages.
