Instructions to use tue-mps/coco_instance_eomt_large_1280 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 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")# Load model directly from transformers import AutoImageProcessor, EomtForUniversalSegmentation processor = AutoImageProcessor.from_pretrained("tue-mps/coco_instance_eomt_large_1280") model = EomtForUniversalSegmentation.from_pretrained("tue-mps/coco_instance_eomt_large_1280") - Notebooks
- Google Colab
- Kaggle
Improve model card: add library, correct pipeline tag, link to project page
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by nielsr HF Staff - opened
README.md
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license: mit
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pipeline_tag: image-segmentation
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This repository contains the model described in [Your ViT is Secretly an Image Segmentation Model](https://huggingface.co/papers/2503.19108).
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license: mit
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pipeline_tag: image-segmentation
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library_name: transformers
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This repository contains the model described in [Your ViT is Secretly an Image Segmentation Model](https://huggingface.co/papers/2503.19108).
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Project page: https://www.tue-mps.org/eomt/
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