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:
- 427cbfce8e94b62aa3ce37d88769d59b2dc8b5ff95b13d4973badd61ae9aca7d
- Size of remote file:
- 346 MB
- SHA256:
- 1178fb02b0360dc02f5b3501f158b29afd4ab2dede1cf7a8c8cececf6a1ddeb3
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