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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
First commit
Browse files- config.json +0 -0
- pytorch_model.bin +3 -0
config.json
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:d2731509b6065382eb61e5338ead0d9f91541705a49375a42fffad90aa706e05
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size 419454079
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