Instructions to use ogimgio/vit-base-highways-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ogimgio/vit-base-highways-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ogimgio/vit-base-highways-2") 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("ogimgio/vit-base-highways-2") model = AutoModelForImageClassification.from_pretrained("ogimgio/vit-base-highways-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b47baa9a2078227746ac133edcfed116448544f027ff96f9ae77a9bc584d7f50
- Size of remote file:
- 3.58 kB
- SHA256:
- 636935bd01c16248261c6e4c3289da61821b60277bda680f09acc2dc8f8baab4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.