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")# pip install -U transformers accelerate # 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
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (d9362ed79be4b77ea758716cdb0fbb9d8ac50e40) Co-authored-by: Nicolas Patry <Narsil@users.noreply.huggingface.co>440309d
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