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🤗 Hugging Face x 🌸 BigScience initiative to create open source community resources for LAMs.

Recent Activity

storytracer  authored a paper about 1 month ago
Towards Best Practices for Open Datasets for LLM Training
davanstrien  new activity about 1 month ago
NationalLibraryOfScotland/encyclopaedia_britannica_illustrated:Update README.md
librarian-bot  updated a dataset about 1 month ago
NationalLibraryOfScotland/encyclopaedia_britannica_illustrated
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biglam's activity

davanstrien 
posted an update 1 day ago
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1740
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
alielfilali01 
posted an update 2 days ago
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497
🚨 Arabic LLM Evaluation 🚨

Few models join the ranking of inceptionai/AraGen-Leaderboard Today.

The new MistralAI model, Saba, is quite impressive, Top10 ! Well done @arthurmensch and team.

Sadly Mistral did not follow its strategy about public weights this time, we hope this changes soon and we get the model with a permissive license.

We added other Mistral models and apparently, we have been sleeping on mistralai/Mistral-Large-Instruct-2411 !

Another impressive model that joined the ranking today is ALLaM-AI/ALLaM-7B-Instruct-preview. After a long wait finally ALLaM is here and it is IMPRESSIVE given its size !

ALLaM is ranked on OALL/Open-Arabic-LLM-Leaderboard as well.
davanstrien 
posted an update 6 days ago
davanstrien 
posted an update 7 days ago
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1827
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 8 days ago
albertvillanova 
posted an update 17 days ago
davanstrien 
posted an update 24 days ago
davanstrien 
posted an update 25 days ago
davanstrien 
posted an update 26 days ago
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2019
🌍 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
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storytracer 
authored a paper about 1 month ago
davanstrien 
in NationalLibraryOfScotland/encyclopaedia_britannica_illustrated about 1 month ago

Update README.md
#2 opened about 1 month ago by
librarian-bot
librarian-bot 
updated a dataset about 1 month ago
librarian-bot 
in NationalLibraryOfScotland/encyclopaedia_britannica_illustrated about 1 month ago

Update README.md
#2 opened about 1 month ago by
librarian-bot
davanstrien 
in NationalLibraryOfScotland/nls_chapbook_illustrations about 1 month ago

Convert dataset to Parquet
#3 opened about 1 month ago by
davanstrien
davanstrien 
updated a dataset about 1 month ago
stefan-it 
in NationalLibraryOfScotland/encyclopaedia_britannica_illustrated about 1 month ago

Convert dataset to Parquet
#1 opened about 1 month ago by
davanstrien
davanstrien 
updated a dataset about 1 month ago
davanstrien 
in NationalLibraryOfScotland/encyclopaedia_britannica_illustrated about 1 month ago

Convert dataset to Parquet
#1 opened about 1 month ago by
davanstrien
davanstrien 
posted an update about 1 month ago
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3068
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
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davanstrien 
posted an update about 1 month ago
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2251
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
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