Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use AhmadHakami/alzheimer-image-classification-google-vit-base-patch16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AhmadHakami/alzheimer-image-classification-google-vit-base-patch16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="AhmadHakami/alzheimer-image-classification-google-vit-base-patch16") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("AhmadHakami/alzheimer-image-classification-google-vit-base-patch16") model = AutoModelForImageClassification.from_pretrained("AhmadHakami/alzheimer-image-classification-google-vit-base-patch16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AhmadHakami/alzheimer-image-classification-google-vit-base-patch16: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/AhmadHakami/alzheimer-image-classification-google-vit-base-patch16/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://AhmadHakami/alzheimer-image-classification-google-vit-base-patch16/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AhmadHakami/alzheimer-image-classification-google-vit-base-patch16/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 675c01b034ff1cbb56e3b6db483e07e20ae5e8811db8bd36b553c0b5d352a363
- Size of remote file:
- 343 MB
- SHA256:
- e2c2c41fa5e1d9d58e01650e8b7eb7fc98066a77bfc1e06c07440381b1e0acd1
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