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:
- ad983687c558169a526e7bbbfa7becebfafd0fd360d43b26e2ba02305085bcac
- Size of remote file:
- 1.37 GB
- SHA256:
- c173e7fd575c4d6c2164621063fed3a0e7e2eb6adbfb7c1845b364bc0fed9ce8
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