Hacktoberfest23 (Hacktoberfest 2023)

posted an update 1 day ago

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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.

davanstrien

posted an update about 1 month ago

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📊 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 about 1 month ago

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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

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davanstrien

posted an update about 2 months ago

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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 about 2 months ago

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

davanstrien

posted an update about 2 months ago

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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 about 2 months ago

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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

davanstrien

posted an update 2 months ago

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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 2 months ago

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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 2 months ago

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🌍 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.

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davanstrien

posted an update 3 months ago

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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

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davanstrien

posted an update 3 months ago

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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

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davanstrien

posted an update 3 months ago

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🇸🇰 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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davanstrien

posted an update 4 months ago

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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

davanstrien

posted an update 4 months ago

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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).

davanstrien

posted an update 5 months ago

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First dataset for the new Hugging Face Bluesky community organisation: https://huggingface.co/datasets/bluesky-community/one-million-bluesky-posts 🦋

📊 1M public posts from Bluesky's firehose API
🔍 Includes text, metadata, and language predictions
🔬 Perfect to experiment with using ML for Bluesky 🤗

Excited to see people build more open tools for a more open social media platform!

davanstrien

posted an update 5 months ago

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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:

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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davanstrien

posted an update 5 months ago

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huggingface.co/DIBT is dead!

Long live

data-is-better-together !

We're working on some very cool projects so we're doing a bit of tidying of the Data is Better Together Hub org 🤓

davanstrien

posted an update 5 months ago

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Excited to see my weird davanstrien/ufo-ColPali dataset featured in a video by @sabrinaesaquino !

The video covers using ColPali with Binary Quantization in Qdant to accelerate retrieval. 2x speed up with no performance drop in results 🛸

Video: https://youtu.be/_A90A-grwIc?si=oB3JAhJG8VQUZGLz
Blog post: https://danielvanstrien.xyz/posts/post-with-code/colpali-qdrant/2024-10-02_using_colpali_with_qdrant.html

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davanstrien

posted an update 6 months ago

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ColPali is an exciting new approach to multimodal document retrieval, but some doubt its practical use with existing vector DBs.

It turns out it's super easy to use Qdrant to index and search ColPali embeddings efficiently.

Blog post here: https://danielvanstrien.xyz/posts/post-with-code/colpali-qdrant/2024-10-02_using_colpali_with_qdrant.html

Very silly demo: davanstrien/ufo-ColPali-Search

Hacktoberfest 2023

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