Instructions to use facebook/mask2former-swin-large-coco-instance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mask2former-swin-large-coco-instance with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="facebook/mask2former-swin-large-coco-instance")# Load model directly from transformers import AutoImageProcessor, Mask2FormerForUniversalSegmentation processor = AutoImageProcessor.from_pretrained("facebook/mask2former-swin-large-coco-instance") model = Mask2FormerForUniversalSegmentation.from_pretrained("facebook/mask2former-swin-large-coco-instance") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db4a715beda2a86bda442b0cbbb1615aacaca1adbd08be706e515dae297ae976
- Size of remote file:
- 866 MB
- SHA256:
- d3c7dd5ff045a75492d496ba0e99169ddb5c4689dc5df0abb310f2dc434cc4b9
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