- efficient batch-wise feature extraction (using a `with` statement for PyTorch models) for custom data pipeline
2.5.1
- added a public batch-wise extraction method to the feature extractor (for custom dataset and data loader classes) - updated README and docs with explanations about how and when to use the mini-batch extraction method - small bug fixes and refactorings
2.5.0
- added method to extractor class for aligning representations using [gLocal](https://proceedings.neurips.cc/paper_files/paper/2023/hash/9febda1c8344cc5f2d51713964864e93-Abstract-Conference.html) - small bug fixes and refactoring
2.4.2
- new DreamSim models - support for CLS token extraction for supervised ViTs
2.4.1
- fixed import issues with DINO models - improved unittests - enhanced modularity of codebase
2.3.18
- integrated DreamSim models into `thingsvision` - small changes to the codebase (more modularity) - minor refactors