The German Commons - 154 Billion Tokens of Openly Licensed Text for German Language Models
Paper
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2510.13996
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Published
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6
AI & ML interests
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christopher
authored
a
paper
9 days ago
thomwolf
authored
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11 days ago
lvwerra
authored
a
paper
13 days ago
Zaid
authored
a
paper
17 days ago
Post
4355
🌎 AI ethics and sustainability are two sides of the same coin.
In our new blog post with Dr. Sasha Luccioni, we argue that separating them (as is too often the case) means missing the bigger picture of how AI systems impact both people and the planet.
Ethical and sustainable AI development can’t be pursued in isolation. The same choices that affect who benefits or is harmed by AI systems also determine how much energy and resources they consume.
We explore how two key concepts, evaluation and transparency, can serve as bridges between these domains:
📊 Evaluation, by moving beyond accuracy or performance metrics to include environmental and social costs, as we’ve done with tools like the AI Energy Score.
🔍 Transparency, by enabling reproducibility, accountability, and environmental reporting through open tools like the Environmental Transparency Space.
AI systems mirror our priorities. If we separate ethics from sustainability, we risk building technologies that are efficient but unjust, or fair but unsustainable.
Read our blog post here: https://huggingface.co/blog/sasha/ethics-sustainability
AIEnergyScore/Leaderboard
sasha/environmental-transparency
In our new blog post with Dr. Sasha Luccioni, we argue that separating them (as is too often the case) means missing the bigger picture of how AI systems impact both people and the planet.
Ethical and sustainable AI development can’t be pursued in isolation. The same choices that affect who benefits or is harmed by AI systems also determine how much energy and resources they consume.
We explore how two key concepts, evaluation and transparency, can serve as bridges between these domains:
📊 Evaluation, by moving beyond accuracy or performance metrics to include environmental and social costs, as we’ve done with tools like the AI Energy Score.
🔍 Transparency, by enabling reproducibility, accountability, and environmental reporting through open tools like the Environmental Transparency Space.
AI systems mirror our priorities. If we separate ethics from sustainability, we risk building technologies that are efficient but unjust, or fair but unsustainable.
Read our blog post here: https://huggingface.co/blog/sasha/ethics-sustainability
AIEnergyScore/Leaderboard
sasha/environmental-transparency
- 1 reply
sasha
authored
3
papers
19 days ago
Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language Model
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2211.02001
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Published
Hype, Sustainability, and the Price of the Bigger-is-Better Paradigm in AI
Paper
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2409.14160
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Published
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3
From Efficiency Gains to Rebound Effects: The Problem of Jevons' Paradox in AI's Polarized Environmental Debate
Paper
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2501.16548
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Published
christopher
posted
an
update
19 days ago
Post
10822
One of the hardest challenges in AI safety is finding the right balance: how do we protect people from harm without undermining their agency? This tension is especially visible in conversational systems, where safeguards can sometimes feel more paternalistic than supportive.
In my latest piece for Hugging Face, I argue that open source and community-driven approaches offer a promising (though not exclusive) way forward.
✨ Transparency can make safety mechanisms into learning opportunities.
✨ Collaboration with diverse communities makes safeguards more relevant across contexts.
✨ Iteration in the open lets protections evolve rather than freeze into rigid, one-size-fits-all rules.
Of course, this isn’t a silver bullet. Top-down safety measures will still be necessary in some cases. But if we only rely on corporate control, we risk building systems that are safe at the expense of trust and autonomy.
Read the blog post here: https://huggingface.co/blog/giadap/preserving-agency
In my latest piece for Hugging Face, I argue that open source and community-driven approaches offer a promising (though not exclusive) way forward.
✨ Transparency can make safety mechanisms into learning opportunities.
✨ Collaboration with diverse communities makes safeguards more relevant across contexts.
✨ Iteration in the open lets protections evolve rather than freeze into rigid, one-size-fits-all rules.
Of course, this isn’t a silver bullet. Top-down safety measures will still be necessary in some cases. But if we only rely on corporate control, we risk building systems that are safe at the expense of trust and autonomy.
Read the blog post here: https://huggingface.co/blog/giadap/preserving-agency
- 7 replies
HugoLaurencon
authored
a
paper
about 1 month ago
mariagrandury
authored
4
papers
about 1 month ago
Adding LLMs to the psycholinguistic norming toolbox: A practical guide to getting the most out of human ratings
Paper
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2509.14405
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Published
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2
Psycholinguistic Word Features: a New Approach for the Evaluation of LLMs Alignment with Humans
Paper
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2506.22439
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Published
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3
Apertus: Democratizing Open and Compliant LLMs for Global Language Environments
Paper
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2509.14233
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Published
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12
La Leaderboard: A Large Language Model Leaderboard for Spanish Varieties and Languages of Spain and Latin America
Paper
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2507.00999
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Published
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1
Post
2843
🤖 As AI-generated content is shared in movies/TV/across the web, there's one simple low-hanging fruit 🍇 to help know what's real: Visible watermarks. With the Gradio team, I've made sure it's trivially easy to add this disclosure to images, video, chatbot text. See how: https://huggingface.co/blog/watermarking-with-gradio
Thanks to the code collab in particular from @abidlabs and Yuvraj Sharma.
Thanks to the code collab in particular from @abidlabs and Yuvraj Sharma.
Post
2363
Tremendous quality of life upgrade on the Hugging Face Hub - we now have auto-complete emojis 🤗 🥳 👏 🙌 🎉
Get ready for lots more very serious analysis on a whole range of topics from yours truly now that we have unlocked this full range of expression 😄 🤔 🗣 🙊
Get ready for lots more very serious analysis on a whole range of topics from yours truly now that we have unlocked this full range of expression 😄 🤔 🗣 🙊
Post
411
I've noticed something. While we're careful about what we post on social media, we're sharing our deepest and most intimate thoughts with AI chatbots -- health concerns, financial worries, relationship issues, business ideas...
With OpenAI hinting at ChatGPT advertising, this matters more than ever. Unlike banner ads, AI advertising happens within the conversation itself. Sponsors could subtly influence that relationship advice or financial guidance.
The good news? We have options.
🤝 Open source AI models let us keep conversations private, avoid surveillance-based business models, and build systems that actually serve users first.
Read more about it in our latest blog post, co-written with
@frimelle
https://huggingface.co/blog/giadap/privacy-conversational-ai
With OpenAI hinting at ChatGPT advertising, this matters more than ever. Unlike banner ads, AI advertising happens within the conversation itself. Sponsors could subtly influence that relationship advice or financial guidance.
The good news? We have options.
🤝 Open source AI models let us keep conversations private, avoid surveillance-based business models, and build systems that actually serve users first.
Read more about it in our latest blog post, co-written with
@frimelle
https://huggingface.co/blog/giadap/privacy-conversational-ai
Post
335
📊 We benchmark models for coding, reasoning, or safety… but what about companionship?
At Hugging Face, we’ve been digging into this question because many of you know how deeply I care about how people build emotional bonds with AI.
That’s why, building on our ongoing research, my amazing co-author and colleague @frimelle created the AI Companionship Leaderboard 🦾
frimelle/companionship-leaderboard
Grounded in our INTIMA benchmark, the leaderboard evaluates models across four dimensions of companionship:
🤖 Assistant Traits: the “voice” and role the model projects
🌷 Relationship & Intimacy: whether it signals closeness or bonding
💘 Emotional Investment: the depth of its emotional engagement
🤲 User Vulnerabilities: how it responds to sensitive disclosures
This work builds on our paper with @frimelle and @yjernite .
📢 Now we’d love your perspective: which open models should we test next for the leaderboard? Drop your suggestions in the comments or reach out! Together we can expand the leaderboard and build a clearer picture of what companionship in AI really looks like.
Paper: INTIMA: A Benchmark for Human-AI Companionship Behavior (2508.09998)
INTIMA Benchmark: AI-companionship/INTIMA
At Hugging Face, we’ve been digging into this question because many of you know how deeply I care about how people build emotional bonds with AI.
That’s why, building on our ongoing research, my amazing co-author and colleague @frimelle created the AI Companionship Leaderboard 🦾
frimelle/companionship-leaderboard
Grounded in our INTIMA benchmark, the leaderboard evaluates models across four dimensions of companionship:
🤖 Assistant Traits: the “voice” and role the model projects
🌷 Relationship & Intimacy: whether it signals closeness or bonding
💘 Emotional Investment: the depth of its emotional engagement
🤲 User Vulnerabilities: how it responds to sensitive disclosures
This work builds on our paper with @frimelle and @yjernite .
📢 Now we’d love your perspective: which open models should we test next for the leaderboard? Drop your suggestions in the comments or reach out! Together we can expand the leaderboard and build a clearer picture of what companionship in AI really looks like.
Paper: INTIMA: A Benchmark for Human-AI Companionship Behavior (2508.09998)
INTIMA Benchmark: AI-companionship/INTIMA
- 1 reply
giadap
authored
a
paper
2 months ago