Instructions to use facebook/maskformer-swin-small-coco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/maskformer-swin-small-coco with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="facebook/maskformer-swin-small-coco")# Load model directly from transformers import AutoImageProcessor, MaskFormerForInstanceSegmentation processor = AutoImageProcessor.from_pretrained("facebook/maskformer-swin-small-coco") model = MaskFormerForInstanceSegmentation.from_pretrained("facebook/maskformer-swin-small-coco", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9bf52c347bcc20681db161395ee6b511a7e3825f60f040f1c7882e99edaf8686
- Size of remote file:
- 253 MB
- SHA256:
- e281b6ab65a335e0a30e13b7a0ae9490f353c16a10af2a7c013bb9b9dcf55970
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