Instructions to use google/vit-base-patch32-224-in21k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/vit-base-patch32-224-in21k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="google/vit-base-patch32-224-in21k")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("google/vit-base-patch32-224-in21k") model = AutoModel.from_pretrained("google/vit-base-patch32-224-in21k") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 477ebfcecdfab2caf492f0c2f362afe25407d8b57d690e48a4c5b4369bf2a7d2
- Size of remote file:
- 352 MB
- SHA256:
- 8f1140419baba006259b9920900ce56f6144db8621bce803b0adafcbeec5bf59
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