Image Classification
Transformers
PyTorch
TensorBoard
vit
vision
Generated from Trainer
Eval Results (legacy)
Instructions to use leejw51/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leejw51/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="leejw51/vit-base-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("leejw51/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("leejw51/vit-base-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7707e1c091a36b3dc7c8cc29255cc6f9b13ee0c3a9c4b6ae34cb6f9ddddf9458
- Size of remote file:
- 343 MB
- SHA256:
- 5b14aa35856f4a4b30775dd82f8fbdff3874a4b21f3c91939f7526cc65c1ee3a
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