Instructions to use bombshelll/swin-brain-abnormalities-classification-fold1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bombshelll/swin-brain-abnormalities-classification-fold1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="bombshelll/swin-brain-abnormalities-classification-fold1") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("bombshelll/swin-brain-abnormalities-classification-fold1") model = AutoModelForImageClassification.from_pretrained("bombshelll/swin-brain-abnormalities-classification-fold1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 21fb8ab0b4743a817ce69d263f301f3f4ece33b568cb3d79d572e6c680f39919
- Size of remote file:
- 5.3 kB
- SHA256:
- 29b9df27d337dbcdd994657a512e19c66d922d4a34e01014bfe292d9076839d7
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