Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Falah/Alzheimer_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Falah/Alzheimer_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Falah/Alzheimer_classification_model") 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("Falah/Alzheimer_classification_model") model = AutoModelForImageClassification.from_pretrained("Falah/Alzheimer_classification_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66ee89ff6d7be19cd4d3aecaa8237d7c43de9cae45b92ff030fba8eee6da506a
- Size of remote file:
- 3.58 kB
- SHA256:
- 61b276eecc484863e86d8294c9a83b8673d1fd1c99118b72e2aeabc975183bdf
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