Image Classification
Transformers
Safetensors
PyTorch
GPShuffleUNet
feature-extraction
medical-imaging
brain-tumor
brain-tumour
mri
brats2020
weakly-supervised-segmentation
segmentation
custom_code
Instructions to use soumickmj/GPShuffleUNet_BraTS2020T1ce_Axial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use soumickmj/GPShuffleUNet_BraTS2020T1ce_Axial with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="soumickmj/GPShuffleUNet_BraTS2020T1ce_Axial", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("soumickmj/GPShuffleUNet_BraTS2020T1ce_Axial", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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