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:
- d071a12399e83c968e42cd9cb262d4dbdef7536de78205858e985890a007242d
- Size of remote file:
- 343 MB
- SHA256:
- 7eef7d216873468bd9fd590d78e1231e44c3bc34d294a36ef2d3756b203163f2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.