Instructions to use tue-mps/coco_instance_eomt_large_1280_dinov3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tue-mps/coco_instance_eomt_large_1280_dinov3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="tue-mps/coco_instance_eomt_large_1280_dinov3")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tue-mps/coco_instance_eomt_large_1280_dinov3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
NiccoloCavagnero
coco_instance_eomt_large_1280_dinov3 checkpoint, refer to the original repository for more information: https://github.com/tue-mps/eomt
9a6a1e7 - Xet hash:
- 2f7c0e9e7775fde26ee686b9262c6b110fb81808216e6d106c26f5640cbe805c
- Size of remote file:
- 1.26 GB
- SHA256:
- 62c25370fcc131dd30169f28bdcf52073969ff2c30f1f9f3892cd9423dd31e40
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