Instructions to use facebook/mask2former-swin-tiny-coco-instance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mask2former-swin-tiny-coco-instance with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="facebook/mask2former-swin-tiny-coco-instance")# Load model directly from transformers import AutoImageProcessor, Mask2FormerForUniversalSegmentation processor = AutoImageProcessor.from_pretrained("facebook/mask2former-swin-tiny-coco-instance") model = Mask2FormerForUniversalSegmentation.from_pretrained("facebook/mask2former-swin-tiny-coco-instance") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af0da5106d16c1ce5745d0e15bef759dc37fa53aa3421fe0ecdbc1799009aba7
- Size of remote file:
- 190 MB
- SHA256:
- 59e7266687f957562d63523de9ad4a1a772a504ef43be4e3935ffb6acdb19161
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