Instructions to use Mahendra42/swin-tiny-patch4-window7-224-finetunedRCC_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mahendra42/swin-tiny-patch4-window7-224-finetunedRCC_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Mahendra42/swin-tiny-patch4-window7-224-finetunedRCC_Classifier") 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("Mahendra42/swin-tiny-patch4-window7-224-finetunedRCC_Classifier") model = AutoModelForImageClassification.from_pretrained("Mahendra42/swin-tiny-patch4-window7-224-finetunedRCC_Classifier") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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oid sha256:1cab772acf76309861b5ffca03b703400bf8d6ce5b3f4ebdad5cbc37a1bcec8c
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size 110342832
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