Image Classification
Transformers
PyTorch
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use johnnydevriese/vit_beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use johnnydevriese/vit_beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="johnnydevriese/vit_beans") 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("johnnydevriese/vit_beans") model = AutoModelForImageClassification.from_pretrained("johnnydevriese/vit_beans") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3590b4da1ed7eb16b93cdc77633ea4330d305771525eef8cb24b4b9ca8adde5
- Size of remote file:
- 343 MB
- SHA256:
- 091b82ea2123c7ccb4de80403f4a1817225d3c9f805ac6dc12c55fb527b7aa5d
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