Instructions to use facebook/dinov2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/dinov2-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="facebook/dinov2-base")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("facebook/dinov2-base") model = AutoModel.from_pretrained("facebook/dinov2-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6e476a7d01463c43c5f765053f4f160f2522fe654d5298e1cc37840c6e7c8fc
- Size of remote file:
- 346 MB
- SHA256:
- 5ad9df1f63b246ed5eecea86eecc24cf816d161e5167564597a3d7d81b3888b0
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