This repository hosts precomputed latent representations (embeddings) extracted from timm image-classification backbones on mnist, 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.
Load with datasets and convert to… See the full description on the dataset page:
https://huggingface.co/datasets/spaicom-lab/semasia-mnist.
