Hugging Face

Hugging Face (Twitter) RT @iScienceLuvr: If you need to know how much time left you have to submit your paper, you can check "AI Conference Deadlines" before there used to be a separate website maintained by PapersWithCode, but since PapersWithCode was shut down, it's now available on HuggingFace

Hugging Face (Twitter) RT @rohanpaul_ai: MASSIVE. THE LARGEST open-sourced pdf data just dropped on @huggingface . Finepdfs 3 trillion tokens across 475 million documents in 1733 languages. This is the largest publicly available corpus sourced exclusively from PDFs, containing about The data was sourced from 105 CommonCrawl snapshots, spanning the summer of 2013 to February 2025, as well as refetched from the internet, and processed using 🏭 datatrove, huggingface's large scale data processing library. This carefully deduplicated and filtered dataset comprises roughly 3.65 terabytes of 3T tokens. For PII and opt-out see Personal and Sensitive Information and opt-out. The dataset is fully reproducible and released under the ODC-By 1.0 license. You will be able to access the reproduction code, ablation and evaluation setup in this GitHub repository soon 👷. Compared to HTML datasets, despite being only mildly filtered, it achieves results nearly on par with... Перейти на оригинальный пост

Hugging Face (Twitter) RT @HuggingPapers: Here's your recap of the hottest AI papers on @huggingface for September 1-7! This week, we dive into LLM comprehension, hallucination, robotics, and more: - Drivel-ology: Challenging LLMs with Interpreting Nonsense with Depth - From Editor to Dense Geometry Estimator - Open Data Synthesis For Deep Research (mentioning @Google Gemini) - Towards a Unified View of Large Language Model Post-Training - ELV-Halluc: Benchmarking Semantic Aggregation Hallucinations in Long Video Understanding - Why Language Models Hallucinate - Robix: A Unified Model for Robot Interaction, Reasoning and Planning (outperforming @OpenAI GPT-4o & @Google Gemini 2.5 Pro) - DeepResearch Arena: The First Exam of LLMs' Research Abilities

‌Hugging Face (Twitter) RT @charlesbben: Recently finished writing a new blogpost about @PyTorch compilation in ZeroGPU Spaces. Worth reading if you're interested in learning about : - PyTorch ahead-of-time compilation - ZeroGPU internals https://huggingface.co/blog/zerogpu-aoti

Hugging Face (Twitter) RT @cgeorgiaw: 🚨 Big news in ML for biotech 🚨 Today, we're launching the Antibody Developability Prediction Competition with @Ginkgo + @huggingface! 💧 Hydrophobicity 🎯 Polyreactivity 🧲 Self-association 🔥 Thermostability 🧪 Titer 🏆 Up to $60k in prizes 📅 Submit by Nov 1, 2025

Hugging Face (Twitter) RT @Thom_Wolf: 3 trillions tokens finely distilled from more than a petabyte of PDF files We’ve just released FinePDF, the latest addition to the Fineweb datasets

Hugging Face (Twitter) RT @LeRobotHF: Almost 10,000 followers here! Let's build the biggest and most active community of Robotics AI builders thanks to open-source!

Hugging Face (Twitter) RT @Thom_Wolf: wow, total BoM cost $660, folks open-source community >> closed source hyped robots

Hugging Face (Twitter) RT @TencentHunyuan: We did it! We now have two models in the top two spots on the @huggingface trending charts. 🥇 Hunyuan-MT-7B 🥈 HunyuanWorld-Voyager Download and deploy the models for free on Hugging Face and GitHub. Your stars and feedback are welcome! 🌟👍❤️ This is just the beginning. Stay tuned for our next open-source release next week!

Hugging Face (Twitter) RT @OfirPress: 3 out of the top 6 most downloaded datasets on @huggingface are SWE-bench related. Thanks!!! ♥️

Hugging Face (Twitter) RT @TrackioApp: Trackio represents @huggingface's effort to democratize experiment tracking for the community: > absolutely free, > open-source, > local-first > drop-in alternative to commercial solutions

Hugging Face (Twitter) RT @maximelabonne: Pheww, another banger dataset from @huggingface! > 3T tokens, 475M PDFs, 1733 languages > Close to Nemotron-CC v2 and FineWeb-Edu+DCLM on its own (‼️) > Greatly boosts perf when combined, likely because it provides high diversity that complements the other datasets well