Instructions to use timm/vit_huge_patch14_224_in21k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/vit_huge_patch14_224_in21k with timm:
import timm model = timm.create_model("hf_hub:timm/vit_huge_patch14_224_in21k", pretrained=True) - Transformers
How to use timm/vit_huge_patch14_224_in21k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="timm/vit_huge_patch14_224_in21k") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/vit_huge_patch14_224_in21k", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b1bac41decbebe771c130c952419d5a2cc4bd05b72ed070939ce7922ed89ce65
- Size of remote file:
- 2.64 GB
- SHA256:
- 44efe50e6b889e919b8cd7feb35b6114a0a75a9bee17bc3597df36a66a3aeab1
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