Instructions to use google/vit-huge-patch14-224-in21k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/vit-huge-patch14-224-in21k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="google/vit-huge-patch14-224-in21k")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("google/vit-huge-patch14-224-in21k") model = AutoModel.from_pretrained("google/vit-huge-patch14-224-in21k") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c1531654eb23b95ee892cefef3defa36901200fc0c830a6904226b8339d184c
- Size of remote file:
- 2.53 GB
- SHA256:
- 4c7c1efdbde7374a23b7ed3dbbd33e945ee5874c2c0e0358e99508b8b7224a5d
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