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_09 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_09 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_09") 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_09") model = AutoModelForImageClassification.from_pretrained("amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_09") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened over 1 year ago
by
SFconvertbot