Instructions to use pphildan/vit-base-patch16-224-v17_4e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pphildan/vit-base-patch16-224-v17_4e with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pphildan/vit-base-patch16-224-v17_4e") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("pphildan/vit-base-patch16-224-v17_4e") model = AutoModelForImageClassification.from_pretrained("pphildan/vit-base-patch16-224-v17_4e") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:e6521ee778e49572e557a08db7433d1918229b8c5a77e4d4dcd4ec7e5fb14a20
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size 343248584
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