Instructions to use devadethanr/alz_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devadethanr/alz_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="devadethanr/alz_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("devadethanr/alz_model") model = AutoModelForImageClassification.from_pretrained("devadethanr/alz_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e780de982572c962e76ce80b0a5f96ca6dcf969a2b77bde71ba3176ff851cda
- Size of remote file:
- 5.05 kB
- SHA256:
- 2c0a0f7e559cc099995b7a8f435f22d3fdc627bd5c8281a75c5444f333b04567
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