Instructions to use Intel/dpt-swinv2-tiny-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/dpt-swinv2-tiny-256 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="Intel/dpt-swinv2-tiny-256")# Load model directly from transformers import AutoImageProcessor, AutoModelForDepthEstimation processor = AutoImageProcessor.from_pretrained("Intel/dpt-swinv2-tiny-256") model = AutoModelForDepthEstimation.from_pretrained("Intel/dpt-swinv2-tiny-256", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7310786c61e110b116458956daf344c56bb927ce63601e83e210f354ad9d7ad9
- Size of remote file:
- 164 MB
- SHA256:
- b11e8b50dee40e953a1c38c9d9330e3bf5512247389b87b74d0c47c263b64983
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