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davanstrienΒ 
posted an update 8 days ago
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2943
πŸ‡ΈπŸ‡° 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
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davanstrienΒ 
posted an update 14 days ago
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1671
Introducing FineWeb-C πŸŒπŸŽ“, 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
dvilasueroΒ 
posted an update 29 days ago
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2281
🌐 Announcing Global-MMLU: an improved MMLU Open dataset with evaluation coverage across 42 languages, built with Argilla and the Hugging Face community.

Global-MMLU is the result of months of work with the goal of advancing Multilingual LLM evaluation. It's been an amazing open science effort with collaborators from Cohere For AI, Mila - Quebec Artificial Intelligence Institute, EPFL, Massachusetts Institute of Technology, AI Singapore, National University of Singapore, KAIST, Instituto Superior TΓ©cnico, Carnegie Mellon University, CONICET, and University of Buenos Aires.

🏷️ +200 contributors used Argilla MMLU questions where regional, dialect, or cultural knowledge was required to answer correctly. 85% of the questions required Western-centric knowledge!

Thanks to this annotation process, the open dataset contains two subsets:

1. πŸ—½ Culturally Agnostic: no specific regional, cultural knowledge is required.
2. βš–οΈ Culturally Sensitive: requires dialect, cultural knowledge or geographic knowledge to answer correctly.

Moreover, we provide high quality translations of 25 out of 42 languages, thanks again to the community and professional annotators leveraging Argilla on the Hub.

I hope this will ensure a better understanding of the limitations and challenges for making open AI useful for many languages.

Dataset: CohereForAI/Global-MMLU
davanstrienΒ 
posted an update about 1 month ago
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505
Increasingly, LLMs are becoming very useful for helping scale annotation tasks, i.e. labelling and filtering. When combined with the structured generation, this can be a very scalable way of doing some pre-annotation without requiring a large team of human annotators.

However, there are quite a few cases where it still doesn't work well. This is a nice paper looking at the limitations of LLM as an annotator for Low Resource Languages: On Limitations of LLM as Annotator for Low Resource Languages (2411.17637).

Humans will still have an important role in the loop to help improve models for all languages (and domains).
davanstrienΒ 
posted an update about 1 month ago
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2481
First dataset for the new Hugging Face Bluesky community organisation: bluesky-community/one-million-bluesky-posts πŸ¦‹

πŸ“Š 1M public posts from Bluesky's firehose API
πŸ” Includes text, metadata, and language predictions
πŸ”¬ Perfect to experiment with using ML for Bluesky πŸ€—

Excited to see people build more open tools for a more open social media platform!
davanstrienΒ 
posted an update about 1 month ago
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1351
The Bluesky AT Protocol unlocks exciting possibilities:
- Building custom feeds using ML
- Creating dashboards for data exploration
- Developing custom models for Bluesky
To gather Bluesky resources on the Hub, I've created a community org: https://huggingface.co/bluesky-community

My first rather modest contribution is a dashboard that shows the number of posts every second. Drinking straight from the firehose API 🚰

bluesky-community/bluesky-posts-over-time
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davanstrienΒ 
posted an update about 2 months ago
dvilasueroΒ 
posted an update about 2 months ago
dvilasueroΒ 
posted an update 2 months ago
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685
Build datasets for AI on the Hugging Face Hubβ€”10x easier than ever!

Today, I'm excited to share our biggest feature since we joined Hugging Face.

Here’s how it works:

1. Pick a datasetβ€”upload your own or choose from 240K open datasets.
2. Paste the Hub dataset ID into Argilla and set up your labeling interface.
3. Share the URL with your team or the whole community!

And the best part? It’s:
- No code – no Python needed
- Integrated – all within the Hub
- Scalable – from solo labeling to 100s of contributors

I am incredibly proud of the team for shipping this after weeks of work and many quick iterations.

Let's make this sentence obsolete: "Everyone wants to do the model work, not the data work."


Read, share, and like the HF blog post:
https://huggingface.co/blog/argilla-ui-hub
davanstrienΒ 
updated a Space 2 months ago
davanstrienΒ 
posted an update 2 months ago
dvilasueroΒ 
posted an update 3 months ago
khawki29Β 
updated a Space 3 months ago