I've created a v1 dataset (
text
I've created a v1 dataset (
https://huggingface.co/datasets/davanstrien/reasoning-required
davanstrien/reasoning-required
dataset
resource
https://huggingface.co/datasets/davanstrien/reasoning-required
) and model (
text
) and model (
https://huggingface.co/davanstrien/ModernBERT-based-Reasoning-Required
davanstrien/ModernBERT-based-Reasoning-Required
model
resource
https://huggingface.co/davanstrien/ModernBERT-based-Reasoning-Required
) to help curate "wild text" data for generating reasoning examples beyond the usual code/math/science domains.
text
) to help curate "wild text" data for generating reasoning examples beyond the usual code/math/science domains.
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new_line
- I developed a "Reasoning Required" dataset with a 0-4 scoring system for reasoning complexity
text
- I developed a "Reasoning Required" dataset with a 0-4 scoring system for reasoning complexity
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- I used educational content from 
text
- I used educational content from 
https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu
HuggingFaceFW/fineweb-edu
dataset
resource
https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu
, adding annotations for domains, reasoning types, and example questions
text
, adding annotations for domains, reasoning types, and example questions
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new_line
My approach enables a more efficient workflow: filter text with small models first, then use LLMs only on high-value content. 
text
My approach enables a more efficient workflow: filter text with small models first, then use LLMs only on high-value content. 
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new_line
This significantly reduces computation costs while expanding reasoning dataset domain coverage. 
text
This significantly reduces computation costs while expanding reasoning dataset domain coverage. 
I've created a v1 dataset (https://huggingface.co/datasets/davanstrien/reasoning-required) and model (https://huggingface.co/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 https://huggingface.co/datasets/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. 
👍
John6666 zarmalhotra onslm