Instructions to use Visual-Attention-Network/van-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Visual-Attention-Network/van-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Visual-Attention-Network/van-large") 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-large", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c825ec52bcf5b1c3f216063a72bd02b341d585f2100bd86529f4df114b1b42d3
- Size of remote file:
- 180 MB
- SHA256:
- 823d81085813ec89c353eb37855181e63a9d6ca6337f06f8425f166f219dd579
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