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stevenbucailleย 
posted an update 2 months ago
Jofthomasย 
posted an update 4 months ago
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4098
The new Mistral 3 models are here !

Today, we announce Mistral 3, the next generation of Mistral models. Mistral 3 includes three state-of-the-art small, dense models (14B, 8B, and 3B) and Mistral Large 3 โ€“ our most capable model to date โ€“ a sparse mixture-of-experts trained with 41B active and 675B total parameters.

All models are released under the Apache 2.0 license.

Ministrals :
https://huggingface.co/collections/mistralai/ministral-3

Mistral Large 3:
https://huggingface.co/collections/mistralai/mistral-large-3
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nouamanetaziย 
posted an update 5 months ago
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4661
After training ๐’๐ฆ๐จ๐ฅ๐‹๐Œ๐Ÿ‘ on ๐Ÿ‘๐Ÿ–๐Ÿ’ ๐‡๐Ÿ๐ŸŽ๐ŸŽ๐ฌ for nearly a month, I've come to realize something most people overlook: ๐ข๐ง๐Ÿ๐ซ๐š๐ฌ๐ญ๐ซ๐ฎ๐œ๐ญ๐ฎ๐ซ๐ž ๐ข๐ฌ ๐ญ๐ก๐ž ๐ฆ๐š๐ค๐ž-๐จ๐ซ-๐›๐ซ๐ž๐š๐ค ๐Ÿ๐š๐œ๐ญ๐จ๐ซ ๐ข๐ง ๐‹๐‹๐Œ ๐ญ๐ซ๐š๐ข๐ง๐ข๐ง๐ . ๐Ÿ”ฅ

Everyone talks about model architecture and data quality. And yes, those matter immensely. But here's what nobody tells you: when your training run fails at 2 AM because of mysterious ๐๐‚๐‚๐‹ ๐ž๐ซ๐ซ๐จ๐ซ๐ฌ, or when your expensive GPU cluster is running at ๐Ÿ”๐ŸŽ% ๐ž๐Ÿ๐Ÿ๐ข๐œ๐ข๐ž๐ง๐œ๐ฒ, the problem isn't your model. It's most probably a ๐ฆ๐ข๐ฌ๐ฎ๐ฌ๐ž ๐จ๐Ÿ ๐ญ๐ก๐ž ๐ก๐š๐ซ๐๐ฐ๐š๐ซ๐ž. ๐Ÿ› ๏ธ

Questions that seemed simple but had no clear answers: Why is ๐Œ๐จ๐„ ๐ญ๐ซ๐š๐ข๐ง๐ข๐ง๐  ๐ฌ๐ฅ๐จ๐ฐ๐ž๐ซ ๐ญ๐ก๐š๐ง ๐๐ž๐ง๐ฌ๐ž ๐ฆ๐จ๐๐ž๐ฅ๐ฌ? Which ๐๐‚๐‚๐‹ ๐Ÿ๐ฅ๐š๐ ๐ฌ should we actually set? How often should we checkpoint without killing throughput?

That's why we built ๐“๐ก๐ž ๐’๐ฆ๐จ๐ฅ ๐“๐ซ๐š๐ข๐ง๐ข๐ง๐  ๐๐ฅ๐š๐ฒ๐›๐จ๐จ๐ค ๐Ÿ“–: a complete guide covering everything from model architecture and data curation to the SmolLM3 training marathon, post-training techniques, and crucially, the ๐ข๐ง๐Ÿ๐ซ๐š๐ฌ๐ญ๐ซ๐ฎ๐œ๐ญ๐ฎ๐ซ๐ž ๐ฅ๐š๐ฒ๐ž๐ซ that most teams get wrong.

We validated real vs theoretical bandwidth across the entire stack: ๐‡๐๐Œ๐Ÿ‘ ๐ก๐ข๐ญ๐ญ๐ข๐ง๐  ๐Ÿ‘ ๐“๐/๐ฌ, ๐๐•๐‹๐ข๐ง๐ค ๐Ÿ’.๐ŸŽ ๐ซ๐ž๐š๐œ๐ก๐ข๐ง๐  ๐Ÿ•๐Ÿ–๐Ÿ” ๐†๐/๐ฌ, ๐๐‚๐ˆ๐ž ๐†๐ž๐ง๐Ÿ’ ๐š๐ญ ๐Ÿ๐Ÿ’.๐Ÿ ๐†๐/๐ฌ. Then we ran collective operations across ๐Ÿ๐Ÿ๐Ÿ– ๐†๐๐”๐ฌ (16 nodes, 8xH100s each) and measured how performance degrades at scale: all-reduce drops from ๐Ÿ’๐Ÿ–๐ŸŽ ๐†๐/๐ฌ on a single node to ๐Ÿ‘๐Ÿ๐ŸŽ-๐Ÿ‘๐Ÿ“๐ŸŽ ๐†๐/๐ฌ across 16 nodes.

If you've ever wondered why your training runs are slower than they should be, or you're planning to scale up and want to avoid expensive mistakes, this guide might save you weeks of debugging.

๐“๐ก๐ž ๐’๐ฆ๐จ๐ฅ ๐“๐ซ๐š๐ข๐ง๐ข๐ง๐  ๐๐ฅ๐š๐ฒ๐›๐จ๐จ๐ค: https://lnkd.in/e5MKXUHS

Shared with โค๏ธ by the HuggingFace team
thomwolfย 
authored a paper 6 months ago
jdelavandeย 
authored a paper 6 months ago
thomwolfย 
authored a paper 9 months ago
m-ricย 
updated a Space 10 months ago
Cidoyiย 
updated a Space 10 months ago
thomwolfย 
authored a paper 10 months ago
m-ricย 
published a Space 10 months ago
Jofthomasย 
posted an update 11 months ago
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4728
Meet our new agentic model : ๐——๐—ฒ๐˜ƒ๐˜€๐˜๐—ฟ๐—ฎ๐—น

Devstral is an open-source LLM built software engineering tasks built under a collaboration between Mistral AI and All Hands AI ๐Ÿ™Œ.

๐—ž๐—ฒ๐˜† ๐—ณ๐—ฒ๐—ฎ๐˜๐˜‚๐—ฟ๐—ฒ๐˜€ :
โ€ข ๐Ÿค– ๐—”๐—ด๐—ฒ๐—ป๐˜๐˜€ : perfect for Agentic coding
โ€ข ๐Ÿƒ ๐—น๐—ถ๐—ด๐—ต๐˜๐˜„๐—ฒ๐—ถ๐—ด๐—ต๐˜: Devstral is a ๐Ÿฎ๐Ÿฐ๐—• parameter based on Mistral small.
โ€ข ยฉ๏ธ ๐—”๐—ฝ๐—ฎ๐—ฐ๐—ต๐—ฒ ๐Ÿฎ.๐Ÿฌ, meaning fully open-source !
โ€ข ๐Ÿ“„ A ๐Ÿญ๐Ÿฎ๐Ÿด๐—ธ context window.

๐Ÿ“šBlog : https://mistral.ai/news/devstral
โšกAPI : The model is also available on our API under the name ๐—ฑ๐—ฒ๐˜ƒ๐˜€๐˜๐—ฟ๐—ฎ๐—น-๐˜€๐—บ๐—ฎ๐—น๐—น-๐Ÿฎ๐Ÿฑ๐Ÿฌ๐Ÿฑ
๐Ÿค— repo : mistralai/Devstral-Small-2505

Can't wait to see what you will build with it !
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thomwolfย 
posted an update 12 months ago
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8267
If you've followed the progress of robotics in the past 18 months, you've likely noticed how robotics is increasingly becoming the next frontier that AI will unlock.

At Hugging Faceโ€”in robotics and across all AI fieldsโ€”we believe in a future where AI and robots are open-source, transparent, and affordable; community-built and safe; hackable and fun. We've had so much mutual understanding and passion working with the Pollen Robotics team over the past year that we decided to join forces!

You can already find our open-source humanoid robot platform Reachy 2 on the Pollen website and the Pollen community and people here on the hub at
pollen-robotics

We're so excited to build and share more open-source robots with the world in the coming months!
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thomwolfย 
authored a paper 12 months ago
nouamanetaziย 
authored a paper 12 months ago
thomwolfย 
authored a paper 12 months ago
thomwolfย 
posted an update about 1 year ago
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3916
The new DeepSite space is really insane for vibe-coders
https://huggingface.co/spaces/enzostvs/deepsite

With the wave of vibe-coding-optimized LLMs like the latest open-source DeepSeek model (version V3-0324), you can basically prompt out-of-the-box and create any app and game in one-shot.

It feels so powerful to me, no more complex framework or under-the-hood prompt engineering to have a working text-to-app tool.

AI is eating the world and *open-source* AI is eating AI itself!

PS: and even more meta is that the DeepSite app and DeepSeek model are both fully open-source code => time to start recursively improve?

PPS: you still need some inference hosting unless you're running the 600B param model at home, so check the very nice list of HF Inference Providers for this model: deepseek-ai/DeepSeek-V3-0324
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thomwolfย 
posted an update about 1 year ago
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3159
We've kept pushing our Open-R1 project, an open initiative to replicate and extend the techniques behind DeepSeek-R1.

And even we were mind-blown by the results we got with this latest model we're releasing: โšก๏ธOlympicCoder ( open-r1/OlympicCoder-7B and open-r1/OlympicCoder-32B)

It's beating Claude 3.7 on (competitive) programming โ€“a domain Anthropic has been historically really strong atโ€“ and it's getting close to o1-mini/R1 on olympiad level coding with just 7B parameters!

And the best part is that we're open-sourcing all about its training dataset, the new IOI benchmark, and more in our Open-R1 progress report #3: https://huggingface.co/blog/open-r1/update-3

Datasets are are releasing:
- open-r1/codeforces
- open-r1/codeforces-cots
- open-r1/ioi
- open-r1/ioi-test-cases
- open-r1/ioi-sample-solutions
- open-r1/ioi-cots
- open-r1/ioi-2024-model-solutions
thomwolfย 
authored a paper about 1 year ago
spisupatย 
authored a paper about 1 year ago
thomwolfย 
authored a paper about 1 year ago