Hugging Face

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Hugging Face

Hugging Face

@huggingface

The AI community building the future. https://t.co/TpiXQMQ9rZ

NYC and Paris and 🌏 Beigetreten Eylül 2016
220 Folgt648K Follower
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Prithiv Sakthi
Prithiv Sakthi@prithivMLmods·
Map-Anything v1 (Universal Feed-Forward Metric 3D Reconstruction) demo is now available on Hugging Face Spaces. Built with @Gradio and integrated with @rerundotio , it performs multi-image and video-based 3D reconstruction, depth, normal map, and interactive measurements.
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Zixuan Li
Zixuan Li@ZixuanLi_·
Don't panic. GLM-5.1 will be open source.
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Lee Robinson
Lee Robinson@leerob·
Yep, Composer 2 started from an open-source base! We will do full pretraining in the future. Only ~1/4 of the compute spent on the final model came from the base, the rest is from our training. This is why evals are very different. And yes, we are following the license through our inference partner terms.
Fynn@fynnso

was messing with the OpenAI base URL in Cursor and caught this accounts/anysphere/models/kimi-k2p5-rl-0317-s515-fast so composer 2 is just Kimi K2.5 with RL at least rename the model ID

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clem 🤗
clem 🤗@ClementDelangue·
Looks like it’s confirmed Cursor’s new model is based on Kimi! It reinforces a couple of things: - open-source keeps being the greatest competition enabler - another validation for chinese open-source that is now the biggest force shaping the global AI stack - the frontier is no longer just about who trains from scratch, but who adapts, fine-tunes, and productizes fastest (seeing the same thing with OpenClaw for example).
Lee Robinson@leerob

Yep, Composer 2 started from an open-source base! We will do full pretraining in the future. Only ~1/4 of the compute spent on the final model came from the base, the rest is from our training. This is why evals are very different. And yes, we are following the license through our inference partner terms.

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Ben Burtenshaw
Ben Burtenshaw@ben_burtenshaw·
cancel your weekend and come fix open source! you can train, build, eval a solution to deal with ai slop in open source repos. icymi, most major os repos are drowning in ai generated prs and issues. it's coming from multiple angles: - well intentioned contributors scaling too fast - students trying out ai tools and not knowing best practices - rampant bots trying to get anything merged we need a solution that allows already resource constrained maintainers to carry on doing their work, without limiting genuine contributors and/or real advancements in ai coding. let's build something that scales and enables folk to contribute more. we don't want to pull up the drawbridge. I made this dataset and pipeline from all the issues and PRs on transformers. It's updated hourly so you can get the latest versions.
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Leandro von Werra
Leandro von Werra@lvwerra·
Excited to release: AgentUI > a fresh chat interface - natively multi-agent > agents coordinate via reports and figures > plug+play any open/closed model as sub-agent > agents specialise in code, web search, multimodal... Try it here: huggingface.co/spaces/lvwerra…
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Sudo su
Sudo su@sudoingX·
this guy has 29 models on huggingface at page 2 ranking. no lab behind him. no sponsorship. $2,000 from his own pocket on GPU rentals. he compressed GLM-4.7 to run on a MacBook and quantized Nemotron Super the week it dropped. all public. all free. nvidia is a trillion dollar company with hundreds of teams but they are not the ones quantizing models middle of the night and pushing them out before sunrise. if nvidia stopped tomorrow their employees stop working. people like @0xSero would not. that is the difference between a paycheck and a mission. @NVIDIAAI you talk about making AI accessible. the people actually doing it are right here. 29 models deep burning their own compute with no ask except more hardware to keep going. you do not need to build another program. just look at who is already building for you. one GPU to this man would produce more public value than a hundred internal sprints. i am not asking for charity. i am asking you to invest in someone who already proved it.
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0xSero@0xSero

Putting out a wish to the universe. I need more compute, if I can get more I will make sure every machine from a small phone to a bootstrapped RTX 3090 node can run frontier intelligence fast with minimal intelligence loss. I have hit page 2 of huggingface, released 3 model family compressions and got GLM-4.7 on a MacBook huggingface.co/0xsero My beast just isn’t enough and I already spent 2k usd on renting GPUs on top of credits provided by Prime intellect and Hotaisle. ——— If you believe in what I do help me get this to Nvidia, maybe they will bless me with the pewter to keep making local AI more accessible 🙏

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clem 🤗
clem 🤗@ClementDelangue·
Talked with @dee_bosa @CNBC about @nvidia and everything open-source AI! Some key points: - Nvidia is the new American open-source AI king - 30% of fortune 500 are using Hugging Face and our goal is to get to the majority of them by the end of the year - Agents will be much more open-source based than chatbots (ex OpenClaw) - Agents empower all to train, fine-tune, and run their own models based on open-source - We crossed 15M AI builders on HF and hope to have as much agents using the platform by the end of the year. Agents are the new users and customers of tech platforms
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Xenova
Xenova@xenovacom·
Not enough people are talking about NVIDIA's new Nemotron-3-Nano (4B) model! 🤯 Hybrid Mamba + Attention architecture, designed as a unified model for reasoning and non-reasoning tasks. So small and efficient, it can run 100% locally in your web browser at 75 tokens per second.
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Maziyar PANAHI
Maziyar PANAHI@MaziyarPanahi·
OpenMed is the #1 most referenced organization powering open-source AI research on Hugging Face. This is the official State of Open Source report, Spring 2026. I started this 8 months ago.
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clem 🤗
clem 🤗@ClementDelangue·
Nvidia just crossed Google as the biggest org on @huggingface with 3,881 team members on the hub. I'm officially calling it: Nvidia is the new American king of open-source AI!
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DailyPapers
DailyPapers@HuggingPapers·
Introducing the Daily Papers SKILL.md Enables agents to > read paper content as markdown > search papers > find linked @huggingface models and datasets > fetch the papers API > and more! Link below ⬇️
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Daniel van Strien
Daniel van Strien@vanstriendaniel·
Is olmOCR-bench getting close to saturation? Top score is now 85.9%. Yesterday @datalabto took #1 with chandra-ocr-2. A year ago, the best was 79. Visualised the race to get there using @huggingface leaderboard data
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Nathan
Nathan@nathanhabib1011·
NEW SOTA OCR MODEL DROPPED Congrats to @VikParuchuri and team for releasing Chandra OCR 2! - 85.9% on olmocr bench, making it first place 🏆 - 90+ language support - 4B model - Full layout information - Extracts + captions images and diagrams - Strong handwriting, math, form, table support Compare every OCR model on the hub and choose the one adapted to your needs 👇
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Mistral AI for Developers
🔥 Meet Mistral Small 4: One model to do it all. ⚡ 128 experts, 119B total parameters, 256k context window ⚡ Configurable Reasoning ⚡ Apache 2.0 ⚡ 40% faster, 3x more throughput Our first model to unify the capabilities of our flagship models into a single, versatile model.
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Unsloth AI
Unsloth AI@UnslothAI·
Introducing Unsloth Studio ✨ A new open-source web UI to train and run LLMs. • Run models locally on Mac, Windows, Linux • Train 500+ models 2x faster with 70% less VRAM • Supports GGUF, vision, audio, embedding models • Auto-create datasets from PDF, CSV, DOCX • Self-healing tool calling and code execution • Compare models side by side + export to GGUF GitHub: github.com/unslothai/unsl… Blog and Guide: unsloth.ai/docs/new/studio Available now on Hugging Face, NVIDIA, Docker and Colab.
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Irene Solaiman
Irene Solaiman@IreneSolaiman·
Open source is having a moment and a lot of those moments happen on Hugging Face We put together a State of Open Source on HF that shows 🚀growth in open models, geographic trends (Chinamaxxing), and some fun tidbits (open source robotics is a next moment...)
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clem 🤗
clem 🤗@ClementDelangue·
We just released an hf CLI extension to detect the best model/quant for a user's hardware and then spins up a local coding agent. Time to go local/private/free/fast for your agents thanks to open-source!
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