Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use oschamp/vit-artworkclassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oschamp/vit-artworkclassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="oschamp/vit-artworkclassifier") 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("oschamp/vit-artworkclassifier") model = AutoModelForImageClassification.from_pretrained("oschamp/vit-artworkclassifier") - Notebooks
- Google Colab
- Kaggle
Commit ·
1979437
1
Parent(s): 8279d63
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (662683fb18e05f72aed610150111166b1d30fd86)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ab72f168678e27a42cf6c7c0632627dc7e39c3e825e9f2946fd8a4c6843b609b
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