Instructions to use varcoder/segformer-b4-crack-segmentation-dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use varcoder/segformer-b4-crack-segmentation-dataset with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="varcoder/segformer-b4-crack-segmentation-dataset")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("varcoder/segformer-b4-crack-segmentation-dataset") model = SegformerForSemanticSegmentation.from_pretrained("varcoder/segformer-b4-crack-segmentation-dataset") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:f63ffd9331311830a94449e596fa6013d46959f92a2cfcce1782cbebaab11705
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size 14884776
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