Instructions to use CondadosAI/mask2former_swin_tiny_coco_instance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CondadosAI/mask2former_swin_tiny_coco_instance with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="CondadosAI/mask2former_swin_tiny_coco_instance")# Load model directly from transformers import AutoImageProcessor, Mask2FormerForUniversalSegmentation processor = AutoImageProcessor.from_pretrained("CondadosAI/mask2former_swin_tiny_coco_instance") model = Mask2FormerForUniversalSegmentation.from_pretrained("CondadosAI/mask2former_swin_tiny_coco_instance") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2bb41b57f23e05dc2ba94c33e56e00053df67cd23ee22ce75c83855a2de3cea7
- Size of remote file:
- 190 MB
- SHA256:
- 3550e8b21381d082c4d12b06a4b7c5f0f4a530125eee4c5f264b1e5f43dfab80
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