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:
- 8620a955e94409a2e2692047c3e31710dbcb65e17b10ab8b8d0a80d3bd9b435a
- Size of remote file:
- 2.93 kB
- SHA256:
- 6c0d68aae790ff88aedeff202530bf75c3a2a55fe38ada4e9312bafdb7e83428
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