Feature Extraction
Transformers
Safetensors
swin
image-feature-extraction
remote-sensing
computer-vision
swin-transformer
building-extraction
change-detection
foundation-model
Instructions to use BiliSakura/RSBuilding-Swin-T with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BiliSakura/RSBuilding-Swin-T with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BiliSakura/RSBuilding-Swin-T")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("BiliSakura/RSBuilding-Swin-T") model = AutoModel.from_pretrained("BiliSakura/RSBuilding-Swin-T") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c7e922728d73b756938371c97b1d6959223be07a0ae0e3f8b3c3ce1d37e6b6d2
- Size of remote file:
- 110 MB
- SHA256:
- 8fc0eb4d63091ee665bdbb8a0c865d1716b96cf8cc1ba1ce60d8b60efd6241ab
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