Omkar2118/datasets huggingface dataset:
NAS-Bench-101

**NAS-Bench-101** is the first public architecture dataset for NAS research. To build NASBench-101, the authors carefully constructed a compact, yet expressive, search space, exploiting graph isomorphisms to identify 423k unique convolutional
architectures. The authors trained and evaluated all of these architectures multiple times on CIFAR-10 and compiled the results into a large dataset of over 5 million trained models. This allows researchers to evaluate the quality of a diverse range of models in milliseconds by querying the precomputed dataset. 

Source: [NAS-Bench-101: Towards Reproducible Neural Architecture Search](/paper/nas-bench-101-towards-reproducible-neural)

Introducing paper: NAS-Bench-101: Towards Reproducible Neural Architecture Search