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:
- cb8c763bd0730b917ebee71694c7e6822eaf858ed0c216dea6f1d80f25c88174
- Size of remote file:
- 3.58 kB
- SHA256:
- 5f19f69255b39e3dca54ec2e5127f416ee781c67799d72ca88ea5a2d5bb9b0c0
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