Instructions to use esvazas/semantic-segmentation-segformer-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use esvazas/semantic-segmentation-segformer-model with Transformers:
# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("esvazas/semantic-segmentation-segformer-model") model = SegformerForSemanticSegmentation.from_pretrained("esvazas/semantic-segmentation-segformer-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eee016053a17eaacae2316947b41396a376c40dc5e4419af6518cc8294cbd2b5
- Size of remote file:
- 15.1 MB
- SHA256:
- ed8ddad89ede6f7ab5155cac72bed03572887094d763d89774696b635f632228
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