Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use IsraNva/isranva with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IsraNva/isranva with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="IsraNva/isranva") 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("IsraNva/isranva") model = AutoModelForImageClassification.from_pretrained("IsraNva/isranva") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4112abf6ad7d0e84f825cf0e29d782c6e6114304109bda4e23971b7442ff06a1
- Size of remote file:
- 343 MB
- SHA256:
- 362103fba34e5ba478f808e996390725b0a91f5393e43f4b71ae460091255add
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