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:
- 0be5fe2173c9178b1ad82f57b8839da0aa946e0bcc3c8c0064a7dd03c1e0c6bf
- Size of remote file:
- 3.45 kB
- SHA256:
- ab8af6b29eb404087346089460439c73ea21969d537e5cddcb8cdf375b09ff52
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