Instructions to use Snarci/ViT-base-patch16-384-Chaoyang-from-scratch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Snarci/ViT-base-patch16-384-Chaoyang-from-scratch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Snarci/ViT-base-patch16-384-Chaoyang-from-scratch") 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("Snarci/ViT-base-patch16-384-Chaoyang-from-scratch") model = AutoModelForImageClassification.from_pretrained("Snarci/ViT-base-patch16-384-Chaoyang-from-scratch") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened over 1 year ago
by
SFconvertbot