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:
- 9a65081625074b235bb1e9d20688a0d7264d41c4e4ec3d2632a1189f875cc069
- Size of remote file:
- 3.58 kB
- SHA256:
- ca602ee267cecec0d48e0335a2d46251aa5d58b45db316e3de683a548fddb77b
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