Instructions to use facebook/mask2former-swin-tiny-cityscapes-semantic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mask2former-swin-tiny-cityscapes-semantic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="facebook/mask2former-swin-tiny-cityscapes-semantic")# Load model directly from transformers import AutoImageProcessor, Mask2FormerForUniversalSegmentation processor = AutoImageProcessor.from_pretrained("facebook/mask2former-swin-tiny-cityscapes-semantic") model = Mask2FormerForUniversalSegmentation.from_pretrained("facebook/mask2former-swin-tiny-cityscapes-semantic") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b5f8ccbbb158ea80ddce29e7a6e16ce04d0eae9a1c4fde0af0d2d92c2faa1e2
- Size of remote file:
- 190 MB
- SHA256:
- 345baec7c8a59c160ed2a30ed13eaa7d394b1195d93b2e6575ef45ab756a05bd
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