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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 4600
Browse files
pytorch_model.bin
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runs/Jul13_18-13-32_5e79d62eb25b/events.out.tfevents.1689272015.5e79d62eb25b.606.1
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