SDbiaseval (Stable Diffusion Bias Eval)

posted an update 10 days ago

Post

2604

📊 Introducing "Hugging Face Dataset Spotlight" 📊

I'm excited to share the first episode of our AI-generated podcast series focusing on nice datasets from the Hugging Face Hub!

This first episode explores mathematical reasoning datasets:

- SynthLabsAI/Big-Math-RL-Verified: Over 250,000 rigorously verified problems spanning multiple difficulty levels and mathematical domains
- open-r1/OpenR1-Math-220k: 220,000 math problems with multiple reasoning traces, verified for accuracy using Math Verify and Llama-3.3-70B models.
- facebook/natural_reasoning: 1.1 million general reasoning questions carefully deduplicated and decontaminated from existing benchmarks, showing superior scaling effects when training models like Llama3.1-8B-Instruct.

Plus a bonus segment on bespokelabs/bespoke-manim!

https://www.youtube.com/watch?v=-TgmRq45tW4

davanstrien

posted an update 10 days ago

Post

3575

Quick POC: Turn a Hugging Face dataset card into a short podcast introducing the dataset using all open models.

I think I'm the only weirdo who would enjoy listening to something like this though 😅

Here is an example for eth-nlped/stepverify

2 replies

·

yjernite

authored a paper 12 days ago

Beyond Release: Access Considerations for Generative AI Systems

Paper • 2502.16701 • Published 14 days ago • 12

davanstrien

posted an update 17 days ago

Post

2571

Hacked together a way to log trl GRPO training completions to a 🤗 dataset repo. This allows you to:

- Track rewards from multiple reward functions
- Treat the completion and rewards from training as a "proper" dataset and do EDA
- Share results for open science

The implementation is super hacky, but I'm curious if people would find this useful.

To push completions to the Hub, you just need two extra parameters:

log_completions=True
log_completions_hub_repo='your-username/repo-name'

Example dataset: davanstrien/test-logs
Colab: https://colab.research.google.com/drive/1wzBFPVthRYYTp-mEYlznLg_e_0Za1M3g

davanstrien

posted an update 22 days ago

Post

2231

Dataset descriptions for trending Hugging Face datasets? Powered by a Smol model davanstrien/Smol-Hub-tldr

davanstrien

posted an update 23 days ago

Post

1897

How do you make 1M+ Hugging Face models & datasets more discoverable?

davanstrien/Smol-Hub-tldr!

I fine-tuned HuggingFaceTB/SmolLM2-360M to generate one-line summaries from a model or dataset README.

Its own self-description?
"A model for generating concise summaries of model & dataset cards from the Hugging Face Hub"

The goal? Make it easier to find the right models and datasets for your specific needs. It's already powering a semantic search for datasets Space.

It's still a WIP but thanks to @loubnabnl , @anton-l , @eliebak et al, for cooking such a nice base model for fine-tuning small, efficient models for specific domains and tasks. 🙏

davanstrien

posted an update 24 days ago

Post

1358

Made some significant updates to my 🤗 semantic datasets search app. If you love falling into a wiki black hole, you might like this...

https://huggingface.co./spaces/librarian-bots/huggingface-datasets-semantic-search

giadap

authored a paper 27 days ago

Fully Autonomous AI Agents Should Not be Developed

Paper • 2502.02649 • Published Feb 4 • 27

giadap

posted an update about 1 month ago

Post

450

From ancient medical ethics to modern AI challenges, the journey of consent represents one of humanity's most fascinating ethical evolutions. In my latest blog post, I explore how we've moved from medical paternalism to a new frontier where AI capabilities force us to rethink consent.

The "consent gap" in AI is real: while we can approve initial data use, AI systems can generate countless unforeseen applications of our personal information. It's like signing a blank check without knowing all possible amounts that could be filled in.

Should we reimagine consent for the AI age? Perhaps we need dynamic consent systems that evolve alongside AI capabilities, similar to how healthcare transformed from physician-centered authority to patient autonomy.

Curious to hear your thoughts: how can we balance technological innovation with meaningful user sovereignty over digital identity?

Read more: https://huggingface.co./blog/giadap/evolution-of-consent

davanstrien

posted an update about 1 month ago

Post

1830

Why choose between strong LLM reasoning and efficient models?

Use DeepSeek to generate high-quality training data, then distil that knowledge into ModernBERT answerdotai/ModernBERT-base for fast, efficient classification.

Blog post: https://danielvanstrien.xyz/posts/2025/deepseek/distil-deepseek-modernbert.html

davanstrien

posted an update about 1 month ago

Post

1932

Updated the ColPali Query Generator Space davanstrien/ColPali-Query-Generator to use Qwen/Qwen2.5-VL-7B-Instruct.

Given an input image, it generates several queries along with explanations to justify them. This approach can generate synthetic data for fine-tuning ColPali models.

davanstrien

posted an update about 1 month ago

Post

2039

🌍 Big step for multilingual AI data!

The Hugging Face community has rated educational content in languages spoken by 1.6 billion people! New additions:
• Japanese
• Italian
• Old High German

Learn more and contribute: https://huggingface.co./blog/davanstrien/fineweb2-community

These ratings can help enhance training data for major world languages.

1 reply

·

meg

posted an update about 2 months ago

Post

3182

💫...And we're live!💫 Seasonal newsletter from ethicsy folks at Hugging Face, exploring the ethics of "AI Agents"
https://huggingface.co./blog/ethics-soc-7
Our analyses found:
- There's a spectrum of "agent"-ness
- *Safety* is a key issue, leading to many other value-based concerns
Read for details & what to do next!
With @evijit , @giadap , and @sasha

yjernite

posted an update about 2 months ago

Post

2314

🤗👤 💻 Speaking of AI agents ...
...Is easier with the right words ;)

My colleagues @meg @evijit @sasha and @giadap just published a wonderful blog post outlining some of the main relevant notions with their signature blend of value-informed and risk-benefits contrasting approach. Go have a read!

https://huggingface.co./blog/ethics-soc-7

davanstrien

posted an update about 2 months ago

Post

3075

Introducing scandi-fine-web-cleaner davanstrien/scandi-fine-web-cleaner, the first model trained on FineWeb-C community annotations!

FineWeb2 is a massive multilingual dataset for pre-training language models. Like any web-scale dataset, it contains low-quality content. How can we improve it?

Over the past months, an amazing community of 400+ annotators has been labelling content quality (using Argilla) across 23 languages through the FineWeb-C initiative.

Today, I'm happy to share the first classifier trained on this data.

🔍 What we've built:

- A lightweight classifier that efficiently removes low-quality content
- 90%+ precision demonstrated on Danish & Swedish
- Can process the 43M+ documents in Danish FineWeb2 with minimal compute

🌍 Why this matters: The approach can be reproduced for any of the 23 languages in FineWeb-C ( data-is-better-together/fineweb-c). We can improve training data quality at scale without massive compute resources by starting with community annotations and training small, efficient classifiers.

Want to build a classifier for your language? Check out the full blog post with code examples and implementation details: https://danielvanstrien.xyz/posts/2025/FineWeb-c/scandinavian-content-filtering-fineweb.html

1 reply

·

davanstrien

posted an update about 2 months ago

Post

2265

The data-is-better-together/fineweb-c dataset is growing!

This week a few more languages have got 1,000 annotations for the educational quality of data from HuggingFaceFW/fineweb-2.

Why should you care?

The quality of pre-training data can have a big impact on the performance of downstream language models trained on that data ( HuggingFaceFW/blogpost-fineweb-v1).

Being able to filter by educational quality is on way of improving the quality of the data you use for training an LLM. Very importantly this approach can also reduce the amount of data needed for pertaining.

Why not use an LLM?

LLMs can be used to annotate educational quality for a subset of data. This data can then be used to train a smaller encoder only model to label the full dataset. However, this may not work well for languages outside of english. This is where fineweb-c (community) comes in.

The community is annotating the educational quality of fineweb2 data. Currently 114 languages have some annotations. These annotations will enable a number of things:

- Evaluate whether an LLM can label the educational quality for texts in that language well
- Directly be used for training quality classifiers
- Help discover other rules and huerisitcs for refining fineweb2 further for different languages.

This week the following languages where done:

Swedish thanks to: @Lauler @AntonVic @ohallstrom @bjarlestam @menbom @Ekgren @apsod

Ukrainian thanks to: @hannayukhymenko @robinhad @realPivo @RabotiahovDmytro @reciprocate

Assamese thanks to: @moyoor97 @Arpanjyoti @nawaf-helmi123 @pahigogoi1 @aelhence @kishorekashyap

Want to learn more: https://huggingface.co./blog/davanstrien/fineweb2-community

Contribute yourself here: data-is-better-together/fineweb-c

1 reply

·

davanstrien

posted an update 2 months ago

Post

3242

🇸🇰 Hovorte po slovensky? Help build better AI for Slovak!

We only need 90 more annotations to include Slovak in the next Hugging Face FineWeb2-C dataset ( data-is-better-together/fineweb-c) release!

Your contribution will help create better language models for 5+ million Slovak speakers.

Annotate here: data-is-better-together/fineweb-c.

Read more about why we're doing it: https://huggingface.co./blog/davanstrien/fineweb2-community

3 replies

·

davanstrien

posted an update 3 months ago

Post

1806

Introducing FineWeb-C 🌐🎓, a community-built dataset for improving language models in ALL languages.

Inspired by FineWeb-Edu the community is labelling the educational quality of texts for many languages.

318 annotators, 32K+ annotations, 12 languages - and growing! 🌍

data-is-better-together/fineweb-c

yjernite

posted an update 3 months ago

Post

2238

🇪🇺 Policy Thoughts in the EU AI Act Implementation 🇪🇺

There is a lot to like in the first draft of the EU GPAI Code of Practice, especially as regards transparency requirements. The Systemic Risks part, on the other hand, is concerning for both smaller developers and for external stakeholders.

I wrote more on this topic ahead of the next draft. TLDR: more attention to immediate large-scale risks and to collaborative solutions supported by evidence can help everyone - as long as developers disclose sufficient information about their design choices and deployment contexts.

Full blog here, based on our submitted response with @frimelle and @brunatrevelin :

https://huggingface.co./blog/yjernite/eu-draft-cop-risks#on-the-proposed-taxonomy-of-systemic-risks