Instructions to use facebook/dpt-dinov2-base-kitti with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/dpt-dinov2-base-kitti with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="facebook/dpt-dinov2-base-kitti")# Load model directly from transformers import AutoImageProcessor, AutoModelForDepthEstimation processor = AutoImageProcessor.from_pretrained("facebook/dpt-dinov2-base-kitti") model = AutoModelForDepthEstimation.from_pretrained("facebook/dpt-dinov2-base-kitti") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23492f0537b3d682e9dd409ba9b267cb8a9768d9e1f76a7f6c1d6189a5beecd6
- Size of remote file:
- 448 MB
- SHA256:
- 85f648db0567d70d2b9434559d1a79c0bdb1d64aca37ae8e59820256d17ff3d1
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