Image Classification
Transformers
PyTorch
TensorBoard
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_06 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_06 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_06") 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("amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_06") model = AutoModelForImageClassification.from_pretrained("amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_06") - Notebooks
- Google Colab
- Kaggle
swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_06 / runs /May25_15-56-58_project /1685030238.78282 /events.out.tfevents.1685030238.project.95612.1
- Xet hash:
- 0fcb59e1064de195176913aa28fff395f29aa5be0d2e90ebe5100bf5057e1ad9
- Size of remote file:
- 6.06 kB
- SHA256:
- 61d3a185f256cecf96b1a08b9cf4579b252b3c2466c0de254ec10335cee27cd5
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