sebasmos/QuantumEmbeddings

Overview This repository provides a collection of embedding datasets for evaluating quantum-classical support vector machines (QSVMs) using embeddings from pre-trained classical models. Each dataset follows the naming convention: <model_name>_<embedding_dim>.csv Where: model_name: the architecture used to generate the embeddings (e.g., vit_b_16, efficientnet, vit_l_14@336px) embedding_dim: the dimensionality of the embedding vectors The last column in each CSV represents the… See the full description on the dataset page: https://huggingface.co/datasets/sebasmos/QuantumEmbeddings.