Instructions to use d4niel92/surface-segmentation-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use d4niel92/surface-segmentation-model with Transformers:
# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("d4niel92/surface-segmentation-model") model = SegformerForSemanticSegmentation.from_pretrained("d4niel92/surface-segmentation-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 594a809ffaddd66c1f61842da8fc8e0b260a914ef73e9c79f3dcd8617820bdd7
- Size of remote file:
- 339 MB
- SHA256:
- a6d8c6fb02f11e7708fb61032db4f6fdf3234c9c43bc03b9d98e5719c3fe3484
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