Instructions to use facebook/dpt-dinov2-base-nyu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/dpt-dinov2-base-nyu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="facebook/dpt-dinov2-base-nyu")# Load model directly from transformers import AutoImageProcessor, AutoModelForDepthEstimation processor = AutoImageProcessor.from_pretrained("facebook/dpt-dinov2-base-nyu") model = AutoModelForDepthEstimation.from_pretrained("facebook/dpt-dinov2-base-nyu") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#3
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:60460ae14c3abc07875faf44f6769811e0a410c7dfb3d9d5b82df909d3f5ad4a
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size 447849116
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