Image Classification
Transformers
PyTorch
TensorBoard
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use Devarshi/Brain_Tumor_Classification_using_swin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Devarshi/Brain_Tumor_Classification_using_swin with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Devarshi/Brain_Tumor_Classification_using_swin") 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("Devarshi/Brain_Tumor_Classification_using_swin") model = AutoModelForImageClassification.from_pretrained("Devarshi/Brain_Tumor_Classification_using_swin") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- be10124e042523e39810519d9f898404be72142b4fd0f8f8883e4eec61cf7b15
- Size of remote file:
- 348 MB
- SHA256:
- 38c61f139340a5eb31459651d406e7e85deb90308d718abe762dcc8f21f4ab2e
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