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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 604b9f5d31046aca55a977c2060e9e310149114263d8a239a29ed1bd6ac610ac
- Size of remote file:
- 348 MB
- SHA256:
- 1ddd2a8069f6b752714793c6eada044e0f61c454dfd4d553d5e09d10abced75d
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