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:
- 00d7220397272c6a74071d43c185446e2c6c76ea8181fcba439680ebabecb6a6
- Size of remote file:
- 189 MB
- SHA256:
- 269fede41807ff5c5a34c98b2db1201a859b94d1a2802687ed8ea7f62f8c4b19
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