Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use raedinkhaled/vit-base-mri with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raedinkhaled/vit-base-mri with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="raedinkhaled/vit-base-mri") 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("raedinkhaled/vit-base-mri") model = AutoModelForImageClassification.from_pretrained("raedinkhaled/vit-base-mri") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#2 opened over 2 years ago
by
librarian-bot
Adding `safetensors` variant of this model
#1 opened about 3 years ago
by
SFconvertbot