Instructions to use Visual-Attention-Network/van-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Visual-Attention-Network/van-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Visual-Attention-Network/van-small") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("Visual-Attention-Network/van-small", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc0bcafe1ed61417b11d6b2be90158948c5fe9c46798a8d5fc010bf53ee41427
- Size of remote file:
- 55.6 MB
- SHA256:
- 909ad0d794bb255317bab1fd6d285f1b2f30e8685805ce64fb139c48d98ae8c4
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