Instructions to use kakaobrain/vit-large-patch16-512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kakaobrain/vit-large-patch16-512 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kakaobrain/vit-large-patch16-512") 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("kakaobrain/vit-large-patch16-512") model = AutoModelForImageClassification.from_pretrained("kakaobrain/vit-large-patch16-512", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da7c853c26f1062abc07a86b55e60468aa1ed2b6f2c043dd47e688a036d5206a
- Size of remote file:
- 1.22 GB
- SHA256:
- 8063ad24a3041d736bb37adc8cf3ce519017c5e6cd0da3fac48e5060eca83321
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