Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use jaypratap/vit-base-patch16-224-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jaypratap/vit-base-patch16-224-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jaypratap/vit-base-patch16-224-classifier") 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("jaypratap/vit-base-patch16-224-classifier") model = AutoModelForImageClassification.from_pretrained("jaypratap/vit-base-patch16-224-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a075aef15a6efea1aa35fbbb5f97cc789991e49d684ed17b9686f60cfecee930
- Size of remote file:
- 4.98 kB
- SHA256:
- adc7857f8bd60e1c0b4b0dac5e5c406c3df2ee29f779ab132d9344c1c8aae679
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