Instructions to use andro-flock/b2-segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andro-flock/b2-segmentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="andro-flock/b2-segmentation")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("andro-flock/b2-segmentation") model = SegformerForSemanticSegmentation.from_pretrained("andro-flock/b2-segmentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39649e7e4bea24d65eaf6089cb18e53b91c115c7228057a0629003ace08f0ee5
- Size of remote file:
- 109 MB
- SHA256:
- 3529b865cae264a86f42ccef78802036c949e12444f78c61e7854fdf7b666b73
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