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")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ahmed792002/vit-plant-classification") model = AutoModelForImageClassification.from_pretrained("ahmed792002/vit-plant-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 164 Bytes
2608031 | 1 2 3 4 5 6 7 8 | {
"size": 224,
"do_normalize": true,
"mean": [0.485, 0.456, 0.406],
"std": [0.229, 0.224, 0.225],
"image_processor_type": "ViTImageProcessor"
}
|