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1024m  authored a paper about 1 hour ago
Improving Multilingual Capabilities with Cultural and Local Knowledge in Large Language Models While Enhancing Native Performance
1024m  authored a paper 5 days ago
Kaleidoscope: In-language Exams for Massively Multilingual Vision Evaluation
loubnabnl  authored a paper 7 days ago
SmolVLM: Redefining small and efficient multimodal models
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merve 
posted an update about 21 hours ago
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1820
sooo many open AI releases past week, let's summarize! 🤗
merve/april-11-releases-67fcd78be33d241c0977b9d2

multimodal
> Moonshot AI released Kimi VL Thinking, first working open-source multimodal reasoning model and Kimi VL Instruct, both 16B MoEs with 3B active params (OS)
> InternVL3 released based on Qwen2.5VL, 7 ckpts with various sizes (1B to 78B)

LLMs
> NVIDIA released Llama-3_1-Nemotron-Ultra-253B-v1 an LLM built on Llama 405B for reasoning, chat and tool use
> Agentica released DeepCoder-14B-Preview, fine-tuned version of DeepSeek-R1-Distilled-Qwen-14B on problem-test pairs, along with the compiled dataset
> Zyphra/ZR1-1.5B is a new small reasoning LLM built on R1-Distill-1.5B (OS)
> Skywork-OR1-32B-Preview is a new reasoning model by Skywork

Image Generation
> HiDream releases three new models, HiDream I1 Dev, I1 Full, and I1 fast for image generation (OS)

*OS ones have Apache 2.0 or MIT licenses
fdaudens 
posted an update 4 days ago
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Want AI that truly understands your country's culture? Public institutions are sitting on the next AI revolution - and here's the practical guide to unlock it.

I've had fascinating conversations recently about sovereign AI, with people trying to solve this recurring question: "How do we build AI that truly understands our culture?"

This guide by @evijit and @yjernite brings lots of insights about this question. It's not just about throwing data at models. It's about partnering cultural expertise with tech infrastructure in ways we're just starting to figure out.

An example? The National Library of Norway already has 150+ AI models on Hugging Face. They're not just digitizing books - they're building AI that thinks in Norwegian, understands Norwegian values, and serves Norwegian citizens.

This is sovereign AI in practice: technology that understands your culture, values, and languages.

Especially loved the practical examples on how to do this:
- Real examples from museums, libraries, and government agencies
- How to convert complex documents (PDFs, PowerPoints) into ML-ready formats
- Code templates for processing public data
- Technical recipes for sharing datasets on open platforms

The stakes? Citizens' ability to leverage their collective digital intelligence.

The technology is ready. The infrastructure exists. The guide shows exactly how to use it. What's needed is your cultural expertise to shape these tools.

Check it out: https://huggingface.co/blog/evijit/public-org-data-ai

P.s.: Building cool projects in a public institution? Share them in the comments for others to learn from!
fdaudens 
posted an update 5 days ago
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Do chatbots lie about Céline Dion? We now have answers, not speculation.

Ai2 just released OLMoTrace and it's a game-changer for transparency. You can literally see where an AI's responses come from in its training data - in real time.

The demo shows results about Céline. So I tried it out myself! Watch what happens in the video.

For journalists, researchers studying hallucinations and anyone who needs to trust their AI, this is like getting X-ray vision into AI systems. When the model made claims, I could instantly verify them against original sources. When it hallucinated, I could see why.

You can finally 1) understand how LLMs actually work and 2) verify if what they're saying is true. No more blind trust.

This pushes the open data movement to the next level.

👉 Blog post: https://allenai.org/blog/olmotrace
👉 Paper: https://www.datocms-assets.com/64837/1743890415-olmotrace.pdf

P.S.: A word of caution: never use a chatbot as a knowledge base. It's not Google. Better use it with a connection to the internet.
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fdaudens 
posted an update 5 days ago
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3967
🎨 Designers, meet OmniSVG! This new model helps you create professional vector graphics from text/images, generate editable SVGs from icons to detailed characters, convert rasters to vectors, maintain style consistency with references, and integrate into your workflow.

@OmniSVG
  • 2 replies
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reach-vb 
authored a paper 7 days ago
fdaudens 
posted an update 8 days ago
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I read the 456-page AI Index report so you don't have to (kidding). The wild part? While AI gets ridiculously more accessible, the power gap is actually widening:

1️⃣ The democratization of AI capabilities is accelerating rapidly:
- The gap between open and closed models is basically closed: difference in benchmarks like MMLU and HumanEval shrunk to just 1.7% in 2024
- The cost to run GPT-3.5-level performance dropped 280x in 2 years
- Model size is shrinking while maintaining performance - Phi-3-mini hitting 60%+ MMLU at fraction of parameters of early models like PaLM

2️⃣ But we're seeing concerning divides deepening:
- Geographic: US private investment ($109B) dwarfs everyone else - 12x China's $9.3B
- Research concentration: US and China dominate highly-cited papers (50 and 34 respectively in 2023), while next closest is only 7
- Gender: Major gaps in AI skill penetration rates - US shows 2.39 vs 1.71 male/female ratio

The tech is getting more accessible but the benefits aren't being distributed evenly. Worth thinking about as these tools become more central to the economy.

Give it a read - fascinating portrait of where AI is heading! https://hai-production.s3.amazonaws.com/files/hai_ai_index_report_2025.pdf
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AtAndDev 
posted an update 9 days ago
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Llama 4 is out...
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fdaudens 
posted an update 9 days ago
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See that purple banner on the Llama 4 models? It's Xet storage, and this is actually huge for anyone building with AI models. Let's geek out a little bit 🤓

Current problem: AI models are massive files using Git LFS. But with models getting bigger and downloads exploding, we needed something better.
Xet lets you version large files like code, with compression and deduplication, all Git-compatible. That means less bandwidth, faster sharing, and smoother collaboration.

Real numbers: ~25% deduplication on Llama 4 models, hitting ~40% for finetunes.

Scale matters here - the Hub served 2B model downloads in 30 days, Llama models alone at 60M. The upcoming Llama 4 Behemoth has 2T parameters! Xet's chunk-based system was built exactly for this.

This is the kind of engineering that makes the next wave of large models actually usable. Kudos to the team! 🧨

Check out the models collection: meta-llama/llama-4-67f0c30d9fe03840bc9d0164
fdaudens 
posted an update 11 days ago
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"Am I going to be replaced by AI?" - Crucial question, but maybe we're asking the wrong one.

📈 There's a statistic from my reads this week that stays with me: Tomer Cohen, LinkedIn's CPO, shares to Jeremy Kahn that 70% of skills used in most jobs will change by 2030. Not jobs disappearing, but transforming. And he calls out bad leadership: "If in one year's time, you are disappointed that your workforce is not 'AI native,' it is your fault."

🔄 Apparently, the Great Recalibration has begun. We're now heading into an era where AI is fundamentally redefining the nature of work itself, by forcing a complete reassessment of human value in the workplace, according to a piece in Fast Company. But it might be driven more by "the need for humans to change the way they work" than AI.

⚡ The Washington Post draws a crucial parallel: We're facing an "AI shock" similar to manufacturing's "China shock" - but hitting knowledge workers. Especially entry-level, white-collar work could get automated. The key difference? "Winning the AI tech competition with other countries won't be enough. It's equally vital to win the battle to re-skill workers."

Digging into these big questions in this week’s AI in the News: https://fdaudens.substack.com/publish/posts/detail/160596301

Also, I'm curious: how are you keeping up with this pace of change? What strategies are working for you?
fdaudens 
posted an update 13 days ago
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Did we just drop personalized AI evaluation?! This tool auto-generates custom benchmarks on your docs to test which models are the best.

Most benchmarks test general capabilities, but what matters is how models handle your data and tasks. YourBench helps answer critical questions like:
- Do you really need a hundreds-of-billions-parameter model sledgehammer to crack a nut?
- Could a smaller, fine-tuned model work better?
- How well do different models understand your domain?

Some cool features:
📚 Generates custom benchmarks from your own documents (PDFs, Word, HTML)
🎯 Tests models on real tasks, not just general capabilities
🔄 Supports multiple models for different pipeline stages
🧠 Generate both single-hop and multi-hop questions
🔍 Evaluate top models and deploy leaderboards instantly
💰 Full cost analysis to optimize for your budget
🛠️ Fully configurable via a single YAML file

26 SOTA models tested for question generation. Interesting finding: Qwen2.5 32B leads in question diversity, while smaller Qwen models and Gemini 2.0 Flash offer great value for cost.

You can also run it locally on any models you want.

I'm impressed. Try it out: yourbench/demo
m-ric 
posted an update 15 days ago
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🚀 DeepSeek R1 moment has come for GUI agents: Rule-based Reinforcement Learning gives better results than SFT with 500x smaller datasets!

Traditionally (by which I mean "in the last few months"), GUI agents have been trained with supervised fine-tuning (SFT). This meant, collecting huge datasets of screen captures from people using computers, and using these to fine-tune your model. 📚

👉 But last week, a new paper introduced UI-R1, applying DeepSeek's R1-style rule-based reinforcement learning (RL) specifically to GUI action prediction tasks.
This is big news: with RL, maybe we could build good agents without the need for huge datasets.

UI-R1 uses a unified reward function that evaluates multiple responses from models, optimizing via policy algorithms like Group Relative Policy Optimization (GRPO).

Specifically, the reward function assesses:
🎯 Action type accuracy: Does the predicted action match the ground truth?
📍 Coordinate accuracy (specifically for clicks): Is the predicted click within the correct bounding box?
📑 Output format: Does the model clearly articulate both its reasoning and final action?

Using just 136 carefully selected mobile tasks—compared to 76,000 tasks for larger models like OS-Atlas—UI-R1 shows significant efficiency and improved performance:
📈 Boosted action prediction accuracy from 76% to 89% on AndroidControl.
🌐 Outperformed larger, SFT-trained models (e.g., OS-Atlas-7B), demonstrating superior results with vastly fewer data points (136 tasks vs. 76K).
🔍 Enhanced adaptability and generalization, excelling even in out-of-domain scenarios.

The paper tests this RL-based method only in low-level GUI tasks. Could it generalize to more complex interactions? 🧐

Read the full paper here 👉 UI-R1: Enhancing Action Prediction of GUI Agents by Reinforcement Learning (2503.21620)
fdaudens 
posted an update 15 days ago
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🔥 DeepSeek vibe coding with DeepSite is going viral with awesome projects!

From games to stunning visualizations, 7 wild examples:

📺 AI TV with custom channels and animations https://x.com/_akhaliq/status/1905747381951545647

🚀 Earth to Moon spacecraft journey visualization
Watch this incredible Three.js space simulation with zero external assets:
https://x.com/_akhaliq/status/1905836902533451999

💣 Minesweeper in 2.5 minutes! Built & deployed instantly on DeepSite. Zero setup needed:
https://x.com/cholf5/status/1906031928937218334

🎮 Asked for Game of Life, got a masterpiece. Simple prompt, complex features. See it in action: https://x.com/pbeyssac/status/1906304454824992844

💫 One-shot anime website with perfect UI. DeepSite turned a simple request into a fully-functional anime site: https://x.com/risphereeditor/status/1905961725028913264

📊 10-minute World Indicators Dashboard. Just described what I wanted and got a full interactive dashboard! https://x.com/i/status/1906345214089785634

✨ Ready to build without coding? Imagine it. Build it. Share it! enzostvs/deepsite
fdaudens 
posted an update 16 days ago
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Want to vibecode with DeepSeek? Just spent 10 minutes with this space and created a full world indicators dashboard - literally just by describing what I wanted!

Anyone can now prototype and deploy projects instantly.

Try out the app: enzostvs/deepsite

My dashboard: fdaudens/world-indicators
osanseviero 
authored a paper 18 days ago
fdaudens 
posted an update 19 days ago
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Want to ramp up your AI skills and start breaking bigger stories? With the Journalists on Hugging Face community, we're launching our first learn-together course!

We'll build AI classifiers that process months of data in minutes. How?

- Work through an interactive version of an excellent course developed by Ben Welsh and Derek Willis
- Share findings and get help in our dedicated community channel
- Build working classifiers you can use in your reporting today

No coding background needed - if you can write a ChatGPT or Claude prompt, you can do this. Journalists are already using these techniques to break stories, from uncovering hidden real estate deals to tracking unusual campaign spending.

Join us—it might give you your next big story!

Thanks to Ben and Derek for letting me adapt their excellent course into this interactive version!

- Check out the course: JournalistsonHF/first-llm-classifier

- Join our Slack community to learn together: https://docs.google.com/forms/d/e/1FAIpQLSfyA7G6Y9q-5hDBSnGc3CFtg9H8fjqKCCuieptXuTqRudGNjQ/viewform
nroggendorff 
posted an update 19 days ago
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I'm not really doing much on HuggingFace right now due to their new Docker space policies, so if you want to keep up with most of what I'm up to, follow my [instagram](https://sly.sh/ig)
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freddyaboulton 
posted an update 21 days ago
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Ever wanted to share your AI creations with friends? ✨

Screenshots are fine, but imagine letting others play with your ACTUAL model!

Introducing Gradio deep links 🔗 - now you can share interactive AI apps, not just images.

Add a gr.DeepLinkButton to any app and get shareable URLs that let ANYONE experiment with your models.
louisbrulenaudet 
posted an update 23 days ago
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I’ve just released logfire-callback on PyPI, designed to facilitate monitoring of Hugging Face Transformer training loops using Pydantic Logfire 🤗

The callback will automatically log training start with configuration parameters, periodic metrics and training completion ⏱️

Install the package using pip:
pip install logfire-callback

First, ensure you have a Logfire API token and set it as an environment variable:
export LOGFIRE_TOKEN=your_logfire_token

Then use the callback in your training code:
from transformers import Trainer, TrainingArguments
from logfire_callback import LogfireCallback

# Initialize your model, dataset, etc.

training_args = TrainingArguments(
    output_dir="./results",
    num_train_epochs=3,
    # ... other training arguments
)

trainer = Trainer(
    model=model,
    args=training_args,
    train_dataset=train_dataset,
    callbacks=[LogfireCallback()]  # Add the Logfire callback here
)

trainer.train()

If you have any feedback, please reach out at @louisbrulenaudet
merve 
posted an update 24 days ago
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So many open releases at Hugging Face past week 🤯 recapping all here ⤵️ merve/march-21-releases-67dbe10e185f199e656140ae

👀 Multimodal
> Mistral AI released a 24B vision LM, both base and instruction FT versions, sota 🔥 (OS)
> with IBM we released SmolDocling, a sota 256M document parser with Apache 2.0 license (OS)
> SpatialLM is a new vision LM that outputs 3D bounding boxes, comes with 0.5B (QwenVL based) and 1B (Llama based) variants
> SkyWork released SkyWork-R1V-38B, new vision reasoning model (OS)

💬 LLMs
> NVIDIA released new Nemotron models in 49B and 8B with their post-training dataset
> LG released EXAONE, new reasoning models in 2.4B, 7.8B and 32B
> Dataset: Glaive AI released a new reasoning dataset of 22M+ examples
> Dataset: NVIDIA released new helpfulness dataset HelpSteer3
> Dataset: OpenManusRL is a new agent dataset based on ReAct framework (OS)
> Open-R1 team released OlympicCoder, new competitive coder model in 7B and 32B
> Dataset: GeneralThought-430K is a new reasoning dataset (OS)

🖼️ Image Generation/Computer Vision
> Roboflow released RF-DETR, new real-time sota object detector (OS) 🔥
> YOLOE is a new real-time zero-shot object detector with text and visual prompts 🥹
> Stability AI released Stable Virtual Camera, a new novel view synthesis model
> Tencent released Hunyuan3D-2mini, new small and fast 3D asset generation model
> ByteDance released InfiniteYou, new realistic photo generation model
> StarVector is a new 8B model that generates svg from images
> FlexWorld is a new model that expands 3D views (OS)

🎤 Audio
> Sesame released CSM-1B new speech generation model (OS)

🤖 Robotics
> NVIDIA released GR00T, new robotics model for generalized reasoning and skills, along with the dataset

*OS ones have Apache 2.0 or MIT license
fdaudens 
posted an update 25 days ago
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🎥 Just tested Stability AI's Stable Virtual Camera - it turns a single photo into dynamic video with AI-powered camera movements! From static meeting room to cinematic sweeps. 🚀

Try it out: stabilityai/stable-virtual-camera