Skip to content


CLIP is not fully supported by Autodistill. Check back later for updates.

DINOv2, developed by Meta Research, is a self-supervised training method for computer vision models. This library uses DINOv2 image embeddings with SVM to build a classification model.

Read the full Autodistill documentation.

Read the DINOv2 Autodistill documentation.


To use DINOv2 with autodistill, you need to install the following dependency:

pip3 install autodistill-dinov2


from autodistill_dinov2 import DINOv2

target_model = DINOv2()

# train a model
# specify the directory where your annotations (in multiclass classification folder format)
# DINOv2 embeddings are saved in a file called "embeddings.json" the folder in which you are working
# with the structure {filename: embedding}

# run inference on the new model
pred = target_model.predict("./context_images_labeled/train/images/dog-7.jpg")