Instructions to use Bwenge840/vit-base-patch16-224-coffee-preloaded with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use Bwenge840/vit-base-patch16-224-coffee-preloaded with timm:
import timm model = timm.create_model("hf_hub:Bwenge840/vit-base-patch16-224-coffee-preloaded", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Bwenge840/vit-base-patch16-224-coffee-preloaded
Vision Transformer coffee image classifier trained with vit_base_patch16_224.
Files
vit_base_patch16_224_coffee_preloaded.pth: PyTorch checkpoint.
This repository contains the PyTorch checkpoint. Re-run the upload with --include-exports to add ONNX/TFLite files.
Expected Input
- RGB image
- Size: 224x224
- Normalization: ImageNet mean
[0.485, 0.456, 0.406], std[0.229, 0.224, 0.225]
Classes
- KR1
- KR10
- KR3
- KR4
- KR5
- KR6
- KR7
- KR8
- KR9
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