Instructions to use Intel/dpt-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/dpt-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="Intel/dpt-large")# Load model directly from transformers import AutoImageProcessor, AutoModelForDepthEstimation processor = AutoImageProcessor.from_pretrained("Intel/dpt-large") model = AutoModelForDepthEstimation.from_pretrained("Intel/dpt-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5654d8c17ab9fee63637bd7ce8979bc618247288afcf18adc2a0f908809715bc
- Size of remote file:
- 1.37 GB
- SHA256:
- 71150941604c39c1c770a72a7b2f56487669f0e3a4d99c8759e233fb1be24080
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