This repository hosts precomputed latent representations (embeddings) extracted from timm image-classification backbones on oxford-flowers, released as part of SEMASIA — a large-scale resource for studying semantic communication, cross-model latent space alignment, and explainability.
Each config corresponds to a single model;
only that model's Parquet files are read on load_dataset.
