Instructions to use philschmid/vit-base-patch16-224-in21k-image-classification-sagemaker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/vit-base-patch16-224-in21k-image-classification-sagemaker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="philschmid/vit-base-patch16-224-in21k-image-classification-sagemaker") 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("philschmid/vit-base-patch16-224-in21k-image-classification-sagemaker") model = AutoModelForImageClassification.from_pretrained("philschmid/vit-base-patch16-224-in21k-image-classification-sagemaker") - Notebooks
- Google Colab
- Kaggle
Upload spModel.h5
#2 opened about 2 years ago
by
shansuja
Adding `safetensors` variant of this model
#1 opened almost 3 years ago
by
SFconvertbot