Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use ulichovick/vit_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ulichovick/vit_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ulichovick/vit_model") 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("ulichovick/vit_model") model = AutoModelForImageClassification.from_pretrained("ulichovick/vit_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b806200dc5da7e4ecbea7685bdcf9e916dcdca66b9e06e5a699ff1c961f2172d
- Size of remote file:
- 343 MB
- SHA256:
- d0286c805ff6920eebf4f84e8362a1de7a9db858e9574412ad18a6c36ca256e1
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