Instructions to use pphildan/vit-base-patch16-224-v22 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pphildan/vit-base-patch16-224-v22 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pphildan/vit-base-patch16-224-v22") 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("pphildan/vit-base-patch16-224-v22") model = AutoModelForImageClassification.from_pretrained("pphildan/vit-base-patch16-224-v22") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 5
Browse files
pytorch_model.bin
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runs/May20_08-56-53_9726b5ef393e/events.out.tfevents.1684573027.9726b5ef393e.1802.6
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