Instructions to use Intel/dpt-large-ade with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/dpt-large-ade with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="Intel/dpt-large-ade")# Load model directly from transformers import AutoImageProcessor, DPTForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("Intel/dpt-large-ade") model = DPTForSemanticSegmentation.from_pretrained("Intel/dpt-large-ade") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d37912e26941ad8b35f56e356bfbcebc72c6f1eca7cde7bdbaf493814b9d9dea
- Size of remote file:
- 1.37 GB
- SHA256:
- cb9106382231b44f797e364a296a98976bf9435b47eecdab2c032b61e6ec7441
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