Image Segmentation
Transformers
PyTorch
Safetensors
segformer
Generated from Trainer
document-image-binarization
Instructions to use DiTo97/binarization-segformer-b3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DiTo97/binarization-segformer-b3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="DiTo97/binarization-segformer-b3")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("DiTo97/binarization-segformer-b3") model = SegformerForSemanticSegmentation.from_pretrained("DiTo97/binarization-segformer-b3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 943c1ff5fc60c0159e73d148eb14354f01a29f05e4a4b0c6e686ce5ba29925da
- Size of remote file:
- 3.96 kB
- SHA256:
- fab86f23740f8fffd410ba1decd48e53ea2bb37b664f16215c79c450ed1262ce
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