SANA-Sprint: One-Step Diffusion with Continuous-Time Consistency Distillation
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Hugging Face OSS Metrics
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sayakpaul
authored
a
paper
3 days ago
Post
540
🤯 Gemma 3's image analysis blew me away!
Tested 2 ways to extract airplane registration numbers from photos with 12B model:
1️⃣ Gradio app w/API link (underrated feature IMO) + ZeroGPU infra on Hugging Face in Google Colab. Fast & free.
2️⃣ LMStudio + local processing (100% private). Running this powerhouse on a MacBook w/16GB RAM is wild! 🚀
Colab: https://colab.research.google.com/drive/1YmmaP0IDEu98CLDppAAK9kbQZ7lFnLZ1?usp=sharing
Tested 2 ways to extract airplane registration numbers from photos with 12B model:
1️⃣ Gradio app w/API link (underrated feature IMO) + ZeroGPU infra on Hugging Face in Google Colab. Fast & free.
2️⃣ LMStudio + local processing (100% private). Running this powerhouse on a MacBook w/16GB RAM is wild! 🚀
Colab: https://colab.research.google.com/drive/1YmmaP0IDEu98CLDppAAK9kbQZ7lFnLZ1?usp=sharing
Post
3983
We just crossed 1,500,000 public models on Hugging Face (and 500k spaces, 330k datasets, 50k papers). One new repository is created every 15 seconds. Congratulations all!
- 3 replies
Post
1157
Ever wanted 45 min with one of AI’s most fascinating minds? Was with
@thomwolf
at HumanX Vegas. Sharing my notes of his Q&A with the press—completely changed how I think about AI’s future:
1️⃣ The next wave of successful AI companies won’t be defined by who has the best model but by who builds the most useful real-world solutions. "We all have engines in our cars, but that’s rarely the only reason we buy one. We expect it to work well, and that’s enough. LLMs will be the same."
2️⃣ Big players are pivoting: "Closed-source companies—OpenAI being the first—have largely shifted from LLM announcements to product announcements."
3️⃣ Open source is changing everything: "DeepSeek was open source AI’s ChatGPT moment. Basically, everyone outside the bubble realized you can get a model for free—and it’s just as good as the paid ones."
4️⃣ Product innovation is being democratized: Take Manus, for example—they built a product on top of Anthropic’s models that’s "actually better than Anthropic’s own product for now, in terms of agents." This proves that anyone can build great products with existing models.
We’re entering a "multi-LLM world," where models are becoming commoditized, and all the tools to build are readily available—just look at the flurry of daily new releases on Hugging Face.
Thom's comparison to the internet era is spot-on: "In the beginning you made a lot of money by making websites... but nowadays the huge internet companies are not the companies that built websites. Like Airbnb, Uber, Facebook, they just use the internet as a medium to make something for real life use cases."
Love to hear your thoughts on this shift!
1️⃣ The next wave of successful AI companies won’t be defined by who has the best model but by who builds the most useful real-world solutions. "We all have engines in our cars, but that’s rarely the only reason we buy one. We expect it to work well, and that’s enough. LLMs will be the same."
2️⃣ Big players are pivoting: "Closed-source companies—OpenAI being the first—have largely shifted from LLM announcements to product announcements."
3️⃣ Open source is changing everything: "DeepSeek was open source AI’s ChatGPT moment. Basically, everyone outside the bubble realized you can get a model for free—and it’s just as good as the paid ones."
4️⃣ Product innovation is being democratized: Take Manus, for example—they built a product on top of Anthropic’s models that’s "actually better than Anthropic’s own product for now, in terms of agents." This proves that anyone can build great products with existing models.
We’re entering a "multi-LLM world," where models are becoming commoditized, and all the tools to build are readily available—just look at the flurry of daily new releases on Hugging Face.
Thom's comparison to the internet era is spot-on: "In the beginning you made a lot of money by making websites... but nowadays the huge internet companies are not the companies that built websites. Like Airbnb, Uber, Facebook, they just use the internet as a medium to make something for real life use cases."
Love to hear your thoughts on this shift!
- 1 reply
lewtun
authored
a
paper
4 days ago
freddyaboulton
posted
an
update
5 days ago
Post
1696
Privacy matters when talking to AI! 🔇
We've just added a microphone mute button to FastRTC in our latest update (v0.0.14). Now you control exactly what your LLM hears.
Plus lots more features in this release! Check them out:
https://github.com/freddyaboulton/fastrtc/releases/tag/0.0.14
We've just added a microphone mute button to FastRTC in our latest update (v0.0.14). Now you control exactly what your LLM hears.
Plus lots more features in this release! Check them out:
https://github.com/freddyaboulton/fastrtc/releases/tag/0.0.14
Post
1901
Introducing OlympicCoder: a series of open reasoning models that can solve olympiad-level programming problems 🧑💻
- 7B open-r1/OlympicCoder-7B
- 32B open-r1/OlympicCoder-32B
We find that OlympicCoder models outperform Claude 3.7 Sonnet, as well as others over 100x larger 💪
Together with the models, we are releasing:
📊CodeForces-CoTs: new dataset of code problems from the most popular competitive coding platform, with R1 traces in C++ and Python open-r1/codeforces-cots
🏆 IOI'2024: a new benchmark of VERY hard programming problems where even frontier models struggle to match human performance open-r1/ioi
For links to the models and datasets, check out our latest progress report from Open R1: https://huggingface.co/blog/open-r1/update-3
- 7B open-r1/OlympicCoder-7B
- 32B open-r1/OlympicCoder-32B
We find that OlympicCoder models outperform Claude 3.7 Sonnet, as well as others over 100x larger 💪
Together with the models, we are releasing:
📊CodeForces-CoTs: new dataset of code problems from the most popular competitive coding platform, with R1 traces in C++ and Python open-r1/codeforces-cots
🏆 IOI'2024: a new benchmark of VERY hard programming problems where even frontier models struggle to match human performance open-r1/ioi
For links to the models and datasets, check out our latest progress report from Open R1: https://huggingface.co/blog/open-r1/update-3
- 1 reply
Post
1703
🔥The Open R1 team just dropped OlympicCoder and it's wild:
- 7B model outperforms Claude 3.7 Sonnet on IOI benchmark (yes, 7B!!)
- 32B crushes all open-weight models tested, even those 100x larger 🤯
Open-sourcing the future of code reasoning! 🚀
Check it out https://huggingface.co/blog/open-r1/update-3
- 7B model outperforms Claude 3.7 Sonnet on IOI benchmark (yes, 7B!!)
- 32B crushes all open-weight models tested, even those 100x larger 🤯
Open-sourcing the future of code reasoning! 🚀
Check it out https://huggingface.co/blog/open-r1/update-3
BrigitteTousi
posted
an
update
5 days ago
Post
3132
LeRobot goes to driving school! 🚗🚗🚗
Hugging Face just announced a new collab with Yaak to bring the largest open-source self-driving dataset to LeRobot!
Major kudos to HF's @cadene , as well as @sandhawalia , @Shnissen and the Yaak team!
Check out the blog post here: https://huggingface.co/blog/lerobot-goes-to-driving-school
Hugging Face just announced a new collab with Yaak to bring the largest open-source self-driving dataset to LeRobot!
Major kudos to HF's @cadene , as well as @sandhawalia , @Shnissen and the Yaak team!
Check out the blog post here: https://huggingface.co/blog/lerobot-goes-to-driving-school
-
- 1 reply
BrigitteTousi
posted
an
update
6 days ago
Post
3624
Regardless of X being down or not, so glad I can rely on HF Posts for AI news ❤️🤗
-
- 1 reply
Post
6265
An assembly of 18 European companies, labs, and universities have banded together to launch 🇪🇺 EuroBERT! It's a state-of-the-art multilingual encoder for 15 European languages, designed to be finetuned for retrieval, classification, etc.
🇪🇺 15 Languages: English, French, German, Spanish, Chinese, Italian, Russian, Polish, Portuguese, Japanese, Vietnamese, Dutch, Arabic, Turkish, Hindi
3️⃣ 3 model sizes: 210M, 610M, and 2.1B parameters - very very useful sizes in my opinion
➡️ Sequence length of 8192 tokens! Nice to see these higher sequence lengths for encoders becoming more common.
⚙️ Architecture based on Llama, but with bi-directional (non-causal) attention to turn it into an encoder. Flash Attention 2 is supported.
🔥 A new Pareto frontier (stronger *and* smaller) for multilingual encoder models
📊 Evaluated against mDeBERTa, mGTE, XLM-RoBERTa for Retrieval, Classification, and Regression (after finetuning for each task separately): EuroBERT punches way above its weight.
📝 Detailed paper with all details, incl. data: FineWeb for English and CulturaX for multilingual data, The Stack v2 and Proof-Pile-2 for code.
Check out the release blogpost here: https://huggingface.co/blog/EuroBERT/release
* EuroBERT/EuroBERT-210m
* EuroBERT/EuroBERT-610m
* EuroBERT/EuroBERT-2.1B
The next step is for researchers to build upon the 3 EuroBERT base models and publish strong retrieval, zero-shot classification, etc. models for all to use. I'm very much looking forward to it!
🇪🇺 15 Languages: English, French, German, Spanish, Chinese, Italian, Russian, Polish, Portuguese, Japanese, Vietnamese, Dutch, Arabic, Turkish, Hindi
3️⃣ 3 model sizes: 210M, 610M, and 2.1B parameters - very very useful sizes in my opinion
➡️ Sequence length of 8192 tokens! Nice to see these higher sequence lengths for encoders becoming more common.
⚙️ Architecture based on Llama, but with bi-directional (non-causal) attention to turn it into an encoder. Flash Attention 2 is supported.
🔥 A new Pareto frontier (stronger *and* smaller) for multilingual encoder models
📊 Evaluated against mDeBERTa, mGTE, XLM-RoBERTa for Retrieval, Classification, and Regression (after finetuning for each task separately): EuroBERT punches way above its weight.
📝 Detailed paper with all details, incl. data: FineWeb for English and CulturaX for multilingual data, The Stack v2 and Proof-Pile-2 for code.
Check out the release blogpost here: https://huggingface.co/blog/EuroBERT/release
* EuroBERT/EuroBERT-210m
* EuroBERT/EuroBERT-610m
* EuroBERT/EuroBERT-2.1B
The next step is for researchers to build upon the 3 EuroBERT base models and publish strong retrieval, zero-shot classification, etc. models for all to use. I'm very much looking forward to it!
- 1 reply
Post
5674
Honored to be named among their 12 pioneers and power players in the news industry in the 2025 Tech Trends Report from Future Today Strategy Group.
Incredible group to be part of - each person is doing groundbreaking work at the intersection of AI and journalism. Worth following them all: they're consistently sharing practical insights on building the future of news.
Take the time to read this report, it's packed with insights as always. The news & information section's #1 insight hits hard: "The most substantive economic impact of AI to date has been licensing payouts for a handful of big publishers. The competition will start shifting in the year ahead to separate AI 'haves' that have positioned themselves to grow from the 'have-nots.'"
This AI-driven divide is something I've been really concerned about. Now is the time to build more than ever!
👉 Full report here: https://ftsg.com/wp-content/uploads/2025/03/FTSG_2025_TR_FINAL_LINKED.pdf
Incredible group to be part of - each person is doing groundbreaking work at the intersection of AI and journalism. Worth following them all: they're consistently sharing practical insights on building the future of news.
Take the time to read this report, it's packed with insights as always. The news & information section's #1 insight hits hard: "The most substantive economic impact of AI to date has been licensing payouts for a handful of big publishers. The competition will start shifting in the year ahead to separate AI 'haves' that have positioned themselves to grow from the 'have-nots.'"
This AI-driven divide is something I've been really concerned about. Now is the time to build more than ever!
👉 Full report here: https://ftsg.com/wp-content/uploads/2025/03/FTSG_2025_TR_FINAL_LINKED.pdf
- 2 replies
Post
7094
I was chatting with
@peakji
, one of the cofounders of Manu AI, who told me he was on Hugging Face (very cool!).
He shared an interesting insight which is that agentic capabilities might be more of an alignment problem rather than a foundational capability issue. Similar to the difference between GPT-3 and InstructGPT, some open-source foundation models are simply trained to 'answer everything in one response regardless of the complexity of the question' - after all, that's the user preference in chatbot use cases. Just a bit of post-training on agentic trajectories can make an immediate and dramatic difference.
As a thank you to the community, he shared 100 invite code first-come first serve, just use “HUGGINGFACE” to get access!
He shared an interesting insight which is that agentic capabilities might be more of an alignment problem rather than a foundational capability issue. Similar to the difference between GPT-3 and InstructGPT, some open-source foundation models are simply trained to 'answer everything in one response regardless of the complexity of the question' - after all, that's the user preference in chatbot use cases. Just a bit of post-training on agentic trajectories can make an immediate and dramatic difference.
As a thank you to the community, he shared 100 invite code first-come first serve, just use “HUGGINGFACE” to get access!
- 6 replies
Post
4648
10,000+ models based on Deepseek R1 have been publicly shared on Hugging Face! Which ones are your favorite ones: https://huggingface.co/models?sort=trending&search=r1. Truly game-changer!
albertvillanova
posted
an
update
10 days ago
Post
3557
🚀 New smolagents update: Safer Local Python Execution! 🦾🐍
With the latest release, we've added security checks to the local Python interpreter: every evaluation is now analyzed for dangerous builtins, modules, and functions. 🔒
Here's why this matters & what you need to know! 🧵👇
1️⃣ Why is local execution risky? ⚠️
AI agents that run arbitrary Python code can unintentionally (or maliciously) access system files, run unsafe commands, or exfiltrate data.
2️⃣ New Safety Layer in smolagents 🛡️
We now inspect every return value during execution:
✅ Allowed: Safe built-in types (e.g., numbers, strings, lists)
⛔ Blocked: Dangerous functions/modules (e.g., os.system, subprocess, exec, shutil)
3️⃣ Immediate Benefits 💡
- Prevent agents from accessing unsafe builtins
- Block unauthorized file or network access
- Reduce accidental security vulnerabilities
4️⃣ Security Disclaimer ⚠️
🚨 Despite these improvements, local Python execution is NEVER 100% safe. 🚨
If you need true isolation, use a remote sandboxed executor like Docker or E2B.
5️⃣ The Best Practice: Use Sandboxed Execution 🔐
For production-grade AI agents, we strongly recommend running code in a Docker or E2B sandbox to ensure complete isolation.
6️⃣ Upgrade Now & Stay Safe! 🚀
Check out the latest smolagents release and start building safer AI agents today.
🔗 https://github.com/huggingface/smolagents
What security measures do you take when running AI-generated code? Let’s discuss! 👇
#AI #smolagents #Python #Security
With the latest release, we've added security checks to the local Python interpreter: every evaluation is now analyzed for dangerous builtins, modules, and functions. 🔒
Here's why this matters & what you need to know! 🧵👇
1️⃣ Why is local execution risky? ⚠️
AI agents that run arbitrary Python code can unintentionally (or maliciously) access system files, run unsafe commands, or exfiltrate data.
2️⃣ New Safety Layer in smolagents 🛡️
We now inspect every return value during execution:
✅ Allowed: Safe built-in types (e.g., numbers, strings, lists)
⛔ Blocked: Dangerous functions/modules (e.g., os.system, subprocess, exec, shutil)
3️⃣ Immediate Benefits 💡
- Prevent agents from accessing unsafe builtins
- Block unauthorized file or network access
- Reduce accidental security vulnerabilities
4️⃣ Security Disclaimer ⚠️
🚨 Despite these improvements, local Python execution is NEVER 100% safe. 🚨
If you need true isolation, use a remote sandboxed executor like Docker or E2B.
5️⃣ The Best Practice: Use Sandboxed Execution 🔐
For production-grade AI agents, we strongly recommend running code in a Docker or E2B sandbox to ensure complete isolation.
6️⃣ Upgrade Now & Stay Safe! 🚀
Check out the latest smolagents release and start building safer AI agents today.
🔗 https://github.com/huggingface/smolagents
What security measures do you take when running AI-generated code? Let’s discuss! 👇
#AI #smolagents #Python #Security
- 2 replies
Post
4053
AI will bring us "a country of yes-men on servers" instead of one of "Einsteins sitting in a data center" if we continue on current trends.
Must-read by @thomwolf deflating overblown AI promises and explaining what real scientific breakthroughs require.
https://thomwolf.io/blog/scientific-ai.html
Must-read by @thomwolf deflating overblown AI promises and explaining what real scientific breakthroughs require.
https://thomwolf.io/blog/scientific-ai.html
- 2 replies
albertvillanova
posted
an
update
11 days ago
Post
3786
🚀 Big news for AI agents! With the latest release of smolagents, you can now securely execute Python code in sandboxed Docker or E2B environments. 🦾🔒
Here's why this is a game-changer for agent-based systems: 🧵👇
1️⃣ Security First 🔐
Running AI agents in unrestricted Python environments is risky! With sandboxing, your agents are isolated, preventing unintended file access, network abuse, or system modifications.
2️⃣ Deterministic & Reproducible Runs 📦
By running agents in containerized environments, you ensure that every execution happens in a controlled and predictable setting—no more environment mismatches or dependency issues!
3️⃣ Resource Control & Limits 🚦
Docker and E2B allow you to enforce CPU, memory, and execution time limits, so rogue or inefficient agents don’t spiral out of control.
4️⃣ Safer Code Execution in Production 🏭
Deploy AI agents confidently, knowing that any generated code runs in an ephemeral, isolated environment, protecting your host machine and infrastructure.
5️⃣ Easy to Integrate 🛠️
With smolagents, you can simply configure your agent to use Docker or E2B as its execution backend—no need for complex security setups!
6️⃣ Perfect for Autonomous AI Agents 🤖
If your AI agents generate and execute code dynamically, this is a must-have to avoid security pitfalls while enabling advanced automation.
⚡ Get started now: https://github.com/huggingface/smolagents
What will you build with smolagents? Let us know! 🚀💡
Here's why this is a game-changer for agent-based systems: 🧵👇
1️⃣ Security First 🔐
Running AI agents in unrestricted Python environments is risky! With sandboxing, your agents are isolated, preventing unintended file access, network abuse, or system modifications.
2️⃣ Deterministic & Reproducible Runs 📦
By running agents in containerized environments, you ensure that every execution happens in a controlled and predictable setting—no more environment mismatches or dependency issues!
3️⃣ Resource Control & Limits 🚦
Docker and E2B allow you to enforce CPU, memory, and execution time limits, so rogue or inefficient agents don’t spiral out of control.
4️⃣ Safer Code Execution in Production 🏭
Deploy AI agents confidently, knowing that any generated code runs in an ephemeral, isolated environment, protecting your host machine and infrastructure.
5️⃣ Easy to Integrate 🛠️
With smolagents, you can simply configure your agent to use Docker or E2B as its execution backend—no need for complex security setups!
6️⃣ Perfect for Autonomous AI Agents 🤖
If your AI agents generate and execute code dynamically, this is a must-have to avoid security pitfalls while enabling advanced automation.
⚡ Get started now: https://github.com/huggingface/smolagents
What will you build with smolagents? Let us know! 🚀💡
Post
2438
Extremely bullish on
@CohereForAI
's Aya Vision (8B & 32B) - new SOTA open-weight VLMs
- 8B wins up to 81% of the time in its class, better than Gemini Flash
- 32B beats Llama 3.2 90B!
- Covers 23 languages, excels in image captioning, VQA & more
- Integrated on transformers from Day 0!
Efficient multimodal models are here to stay!!🔥
Check out their blog! https://huggingface.co/blog/aya-vision
- 8B wins up to 81% of the time in its class, better than Gemini Flash
- 32B beats Llama 3.2 90B!
- Covers 23 languages, excels in image captioning, VQA & more
- Integrated on transformers from Day 0!
Efficient multimodal models are here to stay!!🔥
Check out their blog! https://huggingface.co/blog/aya-vision
Post
5878
Super happy to welcome Nvidia as our latest enterprise hub customer. They have almost 2,000 team members using Hugging Face, and close to 20,000 followers of their org. Can't wait to see what they'll open-source for all of us in the coming months!
Nvidia's org: https://huggingface.co/nvidia
Enterprise hub: https://huggingface.co/enterprise
Nvidia's org: https://huggingface.co/nvidia
Enterprise hub: https://huggingface.co/enterprise
Post
3436
What if AI becomes as ubiquitous as the internet, but runs locally and transparently on our devices?
Fascinating TED talk by @thomwolf on open source AI and its future impact.
Imagine this for AI: instead of black box models running in distant data centers, we get transparent AI that runs locally on our phones and laptops, often without needing internet access. If the original team moves on? No problem - resilience is one of the beauties of open source. Anyone (companies, collectives, or individuals) can adapt and fix these models.
This is a compelling vision of AI's future that solves many of today's concerns around AI transparency and centralized control.
Watch the full talk here: https://www.ted.com/talks/thomas_wolf_what_if_ai_just_works
Fascinating TED talk by @thomwolf on open source AI and its future impact.
Imagine this for AI: instead of black box models running in distant data centers, we get transparent AI that runs locally on our phones and laptops, often without needing internet access. If the original team moves on? No problem - resilience is one of the beauties of open source. Anyone (companies, collectives, or individuals) can adapt and fix these models.
This is a compelling vision of AI's future that solves many of today's concerns around AI transparency and centralized control.
Watch the full talk here: https://www.ted.com/talks/thomas_wolf_what_if_ai_just_works
- 1 reply