A credit-preserving home for datasets, models, examples, and reusable loop artifacts
The Architecture 2.0 Hugging Face space will collect artifacts that help people reproduce and extend AI-assisted architecture loops. It is meant to point to community work, preserve author and institution credit, and make reusable assets easier to discover.
The collection should make artifacts visible without taking credit away from the people who created them.
Workload traces, benchmark packets, simulator outputs, and evidence datasets with clear provenance.
Surrogate models, learned cost models, predictors, and checkpoints that support reviewable architecture loops.
Small loop demos, notebooks, cards, and evidence ledgers that help newcomers understand how the pieces fit.
Every listed artifact should preserve authors, institutions, source links, licenses, papers, and preferred citations.