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")# pip install -U transformers accelerate # 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
Update preprocessor_config.json
Browse files- preprocessor_config.json +1 -1
preprocessor_config.json
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{
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"do_resize":
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"image_mean": [0.5],
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"image_std": [0.5],
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"resample": 2,
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{
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"do_resize": true,
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"image_mean": [0.5],
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"image_std": [0.5],
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"resample": 2,
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