Instructions to use Subh775/Dis-Seg-Former with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Subh775/Dis-Seg-Former with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="Subh775/Dis-Seg-Former")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Subh775/Dis-Seg-Former", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5050f3f4e528c00b185870b54354f02f5cb28165eb89fbc777ad8b6074c4cdc1
- Size of remote file:
- 533 MB
- SHA256:
- e92b681db04618d8f8db633b8083f09d3cb5a5641b42a5be85d6adf35253335f
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