Instructions to use ahmed792002/vit-plant-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmed792002/vit-plant-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ahmed792002/vit-plant-classification") 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("ahmed792002/vit-plant-classification") model = AutoModelForImageClassification.from_pretrained("ahmed792002/vit-plant-classification") - Notebooks
- Google Colab
- Kaggle
Create preprocessor_config.json
Browse files- preprocessor_config.json +7 -0
preprocessor_config.json
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{
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"size": 224,
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"do_normalize": true,
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"mean": [0.485, 0.456, 0.406],
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"std": [0.229, 0.224, 0.225],
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"image_processor_type": "ViTImageProcessor"
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}
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