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:
- 77ef66aff5ec158d850bb0a09a676ab5275be8e8eb719c22a3c2999ca4dfe529
- Size of remote file:
- 343 MB
- SHA256:
- 1ee9d2092ad9c16b0384e679db90abbb92d435c6decec907c425df76cb9ecb6b
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