Instructions to use facebook/dinov2-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/dinov2-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="facebook/dinov2-small")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("facebook/dinov2-small") model = AutoModel.from_pretrained("facebook/dinov2-small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3c1db83916c336fa676a11460ba1a8e41a24bb6cf84e89ae91b960ff00b985a
- Size of remote file:
- 88.3 MB
- SHA256:
- 1051e25b2ed69ddad24f3c41e7b6eed6e7f7d012103ea227e47eb82e87dc2050
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.