Instructions to use google/vit-base-patch16-224-in21k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/vit-base-patch16-224-in21k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="google/vit-base-patch16-224-in21k")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("google/vit-base-patch16-224-in21k") model = AutoModel.from_pretrained("google/vit-base-patch16-224-in21k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from google/vit-base-patch16-224-in21k: direct link, hf CLI and curl.
- Browser
- Download file 346 MB
-
https://huggingface.co/google/vit-base-patch16-224-in21k/resolve/main/model.safetensors
- Command line
-
hf download hf://google/vit-base-patch16-224-in21k/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/google/vit-base-patch16-224-in21k/resolve/main/model.safetensors
346 MB
- Xet hash:
- f07347312676d3600070869948e22211120ab5feac2b73699efc50de8c52bf7d
- Size of remote file:
- 346 MB
- SHA256:
- fd4e1169c7aa6c2dbfa8a6448be13b35abc0ee256190857c90009d12c094619b
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