I-JEPA methodoly teaches a vision transformer model to predict parts of an image in the latent space rather than the pixel space.| DebuggerCafe
Web-SSL 2.0 is a framework to scale DINOv2 models from 1B to 7B parameters by training them in MC-2B (MetaCLIP-2B) dataset.| DebuggerCafe
DINOv2 is a self-supervised computer vision model which learns robust visual features that can be used for downstream tasks.| DebuggerCafe
OpenELM is a family of efficient language models from Apple with completely open-source weights, training, and evaluation code.| DebuggerCafe