biglam/historic-newspaper-illustrations-yolov11
Object Detection
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Updated
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BigLAM: BigScience Libraries, Archives and Museums
non-profit
AI & ML interests
π€ Hugging Face x πΈ BigScience initiative to create open source community resources for LAMs.
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[bot] Conversion to Parquet
#4 opened about 22 hours ago
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parquet-converter
davanstrienΒ
published
a
model
about 13 hours ago
Update README.md
#2 opened about 13 hours ago
by
davanstrien
davanstrienΒ
updated
a
collection
about 14 hours ago
davanstrienΒ
updated
a
Space
about 15 hours ago
make shorter
#2 opened about 15 hours ago
by
davanstrien
Update README.md
#1 opened about 15 hours ago
by
davanstrien
switch to parquet version of dataset
#3 opened 1 day ago
by
davanstrien
Upload dataset
#2 opened 1 day ago
by
davanstrien
Update README.md
#1 opened 1 day ago
by
davanstrien
davanstrienΒ
updated
a
dataset
6 days ago
better README
#2 opened 6 days ago
by
davanstrien
alielfilali01Β
posted
an
update
8 days ago
Post
449
Great efforts from
@AtlasIA
folks to adapt text2image models (ghibli style) for Moroccan Context
Read the blog is here : https://huggingface.co/blog/atlasia/creating-your-custom-ghibli-text-to-image-model
Read the blog is here : https://huggingface.co/blog/atlasia/creating-your-custom-ghibli-text-to-image-model
davanstrienΒ
posted
an
update
16 days ago
Post
1959
Came across a very nice submission from
@marcodsn
for the reasoning datasets competition (https://huggingface.co/blog/bespokelabs/reasoning-datasets-competition).
The dataset distils reasoning chains from arXiv research papers in biology and economics. Some nice features of the dataset:
- Extracts both the logical structure AND researcher intuition from academic papers
- Adopts the persona of researchers "before experiments" to capture exploratory thinking
- Provides multi-short and single-long reasoning formats with token budgets - Shows 7.2% improvement on MMLU-Pro Economics when fine-tuning a 3B model
It's created using the Curator framework with plans to scale across more scientific domains and incorporate multi-modal reasoning with charts and mathematics.
I personally am very excited about datasets like this, which involve creativity in their creation and don't just rely on $$$ to produce a big dataset with little novelty.
Dataset can be found here: marcodsn/academic-chains (give it a like!)
The dataset distils reasoning chains from arXiv research papers in biology and economics. Some nice features of the dataset:
- Extracts both the logical structure AND researcher intuition from academic papers
- Adopts the persona of researchers "before experiments" to capture exploratory thinking
- Provides multi-short and single-long reasoning formats with token budgets - Shows 7.2% improvement on MMLU-Pro Economics when fine-tuning a 3B model
It's created using the Curator framework with plans to scale across more scientific domains and incorporate multi-modal reasoning with charts and mathematics.
I personally am very excited about datasets like this, which involve creativity in their creation and don't just rely on $$$ to produce a big dataset with little novelty.
Dataset can be found here: marcodsn/academic-chains (give it a like!)
albertvillanovaΒ
posted
an
update
17 days ago
Post
2497
smolagents v1.14.0 is out! π
π MCPClient: A sleek new client for connecting to remote MCP servers, making integrations more flexible and scalable.
πͺ¨ Amazon Bedrock: Native support for Bedrock-hosted models.
SmolAgents is now more powerful, flexible, and enterprise-ready. πΌ
Full release π https://github.com/huggingface/smolagents/releases/tag/v1.14.0
#smolagents #LLM #AgenticAI
π MCPClient: A sleek new client for connecting to remote MCP servers, making integrations more flexible and scalable.
πͺ¨ Amazon Bedrock: Native support for Bedrock-hosted models.
SmolAgents is now more powerful, flexible, and enterprise-ready. πΌ
Full release π https://github.com/huggingface/smolagents/releases/tag/v1.14.0
#smolagents #LLM #AgenticAI
gigantΒ
authored
2
papers
23 days ago
davanstrienΒ
posted
an
update
29 days ago
Post
1662
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.
- 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.