Post
258
New blog post alert! "What is the Hugging Face Community Building?", with
@yjernite
and
@irenesolaiman
What 1.8 Million Models Reveal About Open Source Innovation: Our latest deep dive into the Hugging Face Hub reveals patterns that challenge conventional AI narratives:
š Models become platforms for innovation Qwen, Llama, and Gemma models have spawned entire ecosystems of specialized variants. Looking at derivative works shows community adoption better than any single metric.
š Datasets reveal the foundation layer ā Most downloaded datasets are evaluation benchmarks (MMLU, Squad, GLUE) ā Universities and research institutions dominate foundational data ā Domain-specific datasets thrive across finance, healthcare, robotics, and science ā Open actors provide the datasets that power most AI development
šļø Research institutions lead the charge: AI2 (Allen Institute) emerges as one of the most active contributors, alongside significant activity from IBM, NVIDIA, and international organizations. The open source ecosystem spans far beyond Big Tech.
š Interactive exploration tools: We've built several tools to help you discover patterns!
ModelVerse Explorer - organizational contributions
DataVerse Explorer - dataset patterns
Organization HeatMap - activity over time
Base Model Explorer - model family trees
Semantic Search - find models by capability
š Academic research is thriving: Researchers are already producing valuable insights, including recent work at FAccT 2025: "The Brief and Wondrous Life of Open Models." We've also made hub datasets, weekly snapshots, and other data available for your own analysis.
The bottom line: AI development is far more distributed, diverse, and collaborative than popular narratives suggest. Real innovation happens through community collaboration across specialized domains.
Read: https://huggingface.co/blog/evijit/hf-hub-ecosystem-overview
What 1.8 Million Models Reveal About Open Source Innovation: Our latest deep dive into the Hugging Face Hub reveals patterns that challenge conventional AI narratives:
š Models become platforms for innovation Qwen, Llama, and Gemma models have spawned entire ecosystems of specialized variants. Looking at derivative works shows community adoption better than any single metric.
š Datasets reveal the foundation layer ā Most downloaded datasets are evaluation benchmarks (MMLU, Squad, GLUE) ā Universities and research institutions dominate foundational data ā Domain-specific datasets thrive across finance, healthcare, robotics, and science ā Open actors provide the datasets that power most AI development
šļø Research institutions lead the charge: AI2 (Allen Institute) emerges as one of the most active contributors, alongside significant activity from IBM, NVIDIA, and international organizations. The open source ecosystem spans far beyond Big Tech.
š Interactive exploration tools: We've built several tools to help you discover patterns!
ModelVerse Explorer - organizational contributions
DataVerse Explorer - dataset patterns
Organization HeatMap - activity over time
Base Model Explorer - model family trees
Semantic Search - find models by capability
š Academic research is thriving: Researchers are already producing valuable insights, including recent work at FAccT 2025: "The Brief and Wondrous Life of Open Models." We've also made hub datasets, weekly snapshots, and other data available for your own analysis.
The bottom line: AI development is far more distributed, diverse, and collaborative than popular narratives suggest. Real innovation happens through community collaboration across specialized domains.
Read: https://huggingface.co/blog/evijit/hf-hub-ecosystem-overview
