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Post
3708
What are you using to evaluate models or AI systems? So far we're building lighteval & leaderboards on the hub but still feels early & a lot more to build. What would be useful to you?
- 6 replies
Post
1527
LeRobot-worldwide-hackathon
is already scheduled in 30 cities all over the world! Check if there's one in your city here: LeRobot-worldwide-hackathon/worldwide-map
Post
1434
The
meta-llama
org just crossed 40,000 followers on Hugging Face. Grateful for all their impact on the field sharing the Llama weights openly and much more!
We need more of this from all other big tech to make the AI more open, collaborative and beneficial to all!
meta-llama
org just crossed 40,000 followers on Hugging Face. Grateful for all their impact on the field sharing the Llama weights openly and much more! We need more of this from all other big tech to make the AI more open, collaborative and beneficial to all!
davanstrienΒ
posted
an
update
16 days ago
Post
1960
Came across a very nice submission from
@marcodsn
for the reasoning datasets competition (https://huggingface.co/blog/bespokelabs/reasoning-datasets-competition).
The dataset distils reasoning chains from arXiv research papers in biology and economics. Some nice features of the dataset:
- Extracts both the logical structure AND researcher intuition from academic papers
- Adopts the persona of researchers "before experiments" to capture exploratory thinking
- Provides multi-short and single-long reasoning formats with token budgets - Shows 7.2% improvement on MMLU-Pro Economics when fine-tuning a 3B model
It's created using the Curator framework with plans to scale across more scientific domains and incorporate multi-modal reasoning with charts and mathematics.
I personally am very excited about datasets like this, which involve creativity in their creation and don't just rely on $$$ to produce a big dataset with little novelty.
Dataset can be found here: marcodsn/academic-chains (give it a like!)
The dataset distils reasoning chains from arXiv research papers in biology and economics. Some nice features of the dataset:
- Extracts both the logical structure AND researcher intuition from academic papers
- Adopts the persona of researchers "before experiments" to capture exploratory thinking
- Provides multi-short and single-long reasoning formats with token budgets - Shows 7.2% improvement on MMLU-Pro Economics when fine-tuning a 3B model
It's created using the Curator framework with plans to scale across more scientific domains and incorporate multi-modal reasoning with charts and mathematics.
I personally am very excited about datasets like this, which involve creativity in their creation and don't just rely on $$$ to produce a big dataset with little novelty.
Dataset can be found here: marcodsn/academic-chains (give it a like!)
Post
3970
Energy is a massive constraint for AI but do you even know what energy your chatGPT convos are using?
We're trying to change this by releasing ChatUI-energy, the first interface where you see in real-time what energy your AI conversations consume. Great work from @jdelavande powered by spaces & TGI, available for a dozen of open-source models like Llama, Mistral, Qwen, Gemma and more.
jdelavande/chat-ui-energy
Should all chat interfaces have this? Just like ingredients have to be shown on products you buy, we need more transparency in AI for users!
We're trying to change this by releasing ChatUI-energy, the first interface where you see in real-time what energy your AI conversations consume. Great work from @jdelavande powered by spaces & TGI, available for a dozen of open-source models like Llama, Mistral, Qwen, Gemma and more.
jdelavande/chat-ui-energy
Should all chat interfaces have this? Just like ingredients have to be shown on products you buy, we need more transparency in AI for users!
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- 3 replies
Post
2928
Just crossed half a million public apps on Hugging Face. A new public app is created every minute these days π€―π€―π€―
What's your favorite? http://hf.co/spaces
What's your favorite? http://hf.co/spaces
- 3 replies
Post
1466
You can now bill your inference costs from all our inference partners (together, fireworks, fal, sambanova, cerebras, hyperbolic,...) to your Hugging Face organization.
Useful to drive more company-wide usage of AI without the billing headaches!
Useful to drive more company-wide usage of AI without the billing headaches!
- 1 reply
davanstrienΒ
posted
an
update
29 days ago
Post
1662
I've created a v1 dataset (
davanstrien/reasoning-required) and model (
davanstrien/ModernBERT-based-Reasoning-Required) to help curate "wild text" data for generating reasoning examples beyond the usual code/math/science domains.
- I developed a "Reasoning Required" dataset with a 0-4 scoring system for reasoning complexity
- I used educational content from HuggingFaceFW/fineweb-edu, adding annotations for domains, reasoning types, and example questions
My approach enables a more efficient workflow: filter text with small models first, then use LLMs only on high-value content.
This significantly reduces computation costs while expanding reasoning dataset domain coverage.
- I developed a "Reasoning Required" dataset with a 0-4 scoring system for reasoning complexity
- I used educational content from HuggingFaceFW/fineweb-edu, adding annotations for domains, reasoning types, and example questions
My approach enables a more efficient workflow: filter text with small models first, then use LLMs only on high-value content.
This significantly reduces computation costs while expanding reasoning dataset domain coverage.
BrigitteTousiΒ
posted
an
update
about 1 month ago
Post
3062
AI agents are transforming how we interact with technology, but how sustainable are they? π
Design choices β like model size and structure β can massively impact energy use and cost. β‘π° The key takeaway: smaller, task-specific models can be far more efficient than large, general-purpose ones.
π Open-source models offer greater transparency, allowing us to track energy consumption and make more informed decisions on deployment. π± Open-source = more efficient, eco-friendly, and accountable AI.
Read our latest, led by @sasha with assists from myself + @yjernite π€
https://huggingface.co/blog/sasha/ai-agent-sustainability
Design choices β like model size and structure β can massively impact energy use and cost. β‘π° The key takeaway: smaller, task-specific models can be far more efficient than large, general-purpose ones.
π Open-source models offer greater transparency, allowing us to track energy consumption and make more informed decisions on deployment. π± Open-source = more efficient, eco-friendly, and accountable AI.
Read our latest, led by @sasha with assists from myself + @yjernite π€
https://huggingface.co/blog/sasha/ai-agent-sustainability
- 1 reply
Post
2655
Llama 4 is in transformers!
Fun example using the instruction-tuned Maverick model responding about two images, using tensor parallel for maximum speed.
From https://huggingface.co/blog/llama4-release
Fun example using the instruction-tuned Maverick model responding about two images, using tensor parallel for maximum speed.
From https://huggingface.co/blog/llama4-release
- 1 reply
Post
1994
Llama models (arguably the most successful open AI models of all times) just represented 3% of total model downloads on Hugging Face in March.
People and media like stories of winner takes all & one model/company to rule them all but the reality is much more nuanced than this!
Kudos to all the small AI builders out there!
People and media like stories of winner takes all & one model/company to rule them all but the reality is much more nuanced than this!
Kudos to all the small AI builders out there!
- 2 replies
Post
1355
Now in Enterprise Hub organizations, you can centralize your billing not only for HF usage but also inference through our inference partners.
Will prevent some headaches for your finance & accounting teams haha (so feel free to share that with them).
Will prevent some headaches for your finance & accounting teams haha (so feel free to share that with them).
- 3 replies
Post
4029
Before 2020, most of the AI field was open and collaborative. For me, that was the key factor that accelerated scientific progress and made the impossible possibleβjust look at the βTβ in ChatGPT, which comes from the Transformer architecture openly shared by Google.
Then came the myth that AI was too dangerous to share, and companies started optimizing for short-term revenue. That led many major AI labs and researchers to stop sharing and collaborating.
With OAI and sama now saying they're willing to share open weights again, we have a real chance to return to a golden age of AI progress and democratizationβpowered by openness and collaboration, in the US and around the world.
This is incredibly exciting. Letβs go, open science and open-source AI!
Then came the myth that AI was too dangerous to share, and companies started optimizing for short-term revenue. That led many major AI labs and researchers to stop sharing and collaborating.
With OAI and sama now saying they're willing to share open weights again, we have a real chance to return to a golden age of AI progress and democratizationβpowered by openness and collaboration, in the US and around the world.
This is incredibly exciting. Letβs go, open science and open-source AI!
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- 5 replies
Post
2422
What's this cool purple banner haha πΆπΆπΆ
- 4 replies
Post
2253
Very interesting security section by
@yjernite
@lvwerra
@reach-vb
@dvilasuero
& the team replicating R1. Broadly applicable to most open-source models & some to APIs (but APIs have a lot more additional risks because you're not in control of the underlying system):
https://huggingface.co/blog/open-r1/update-4#is-it-safe
https://huggingface.co/blog/open-r1/update-4#is-it-safe
- 1 reply
Post
1581
A repository is created every ~15 secs on Hugging Face so
@kramp
added a "Getting Started" to make it easier & a model release checklist: https://huggingface.co/docs/hub/model-release-checklist
What are you uploading today?
What are you uploading today?
- 1 reply
Post
3746
Should we assemble affordable open-source robots at Hugging Face for the community. Would you buy them? At what price?
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- 8 replies
Post
2603
Nice new space to see how fast your personal or organization followers are growing on HF:
julien-c/follow-history
As you can see, I still have more followers than @julien-c even if he's trying to change this by building such cool spaces πππ
julien-c/follow-history
As you can see, I still have more followers than @julien-c even if he's trying to change this by building such cool spaces πππ
Post
4671
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