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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
update model card README.md
7e1a7a0 -
Model save
ee4d73a -
Training in progress, epoch 5
d10a801 -
Training in progress, epoch 4
5bf026e -
Training in progress, epoch 3
1d4aabf -
Training in progress, epoch 2
16b465b -
Training in progress, epoch 1
75fdb6d -
initial commit
4308b68