Instructions to use prithivMLmods/Alzheimer-Stage-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Alzheimer-Stage-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Alzheimer-Stage-Classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Alzheimer-Stage-Classifier") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Alzheimer-Stage-Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-2124/optimizer.pt from prithivMLmods/Alzheimer-Stage-Classifier: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/prithivMLmods/Alzheimer-Stage-Classifier/resolve/main/checkpoint-2124/optimizer.pt
- Command line
-
hf download hf://prithivMLmods/Alzheimer-Stage-Classifier/checkpoint-2124/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/prithivMLmods/Alzheimer-Stage-Classifier/resolve/main/checkpoint-2124/optimizer.pt
687 MB
- Xet hash:
- e1d118941aba029e326ab09032c6a051fbf44199d5f14b3fe66331beb61b85d8
- Size of remote file:
- 687 MB
- SHA256:
- 65f6396a8aaf558ca64fa52db7950300d1c165bcd4b2753ce70e4c6e258b06aa
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