Instructions to use dewanakl/batik-vit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dewanakl/batik-vit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dewanakl/batik-vit") 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("dewanakl/batik-vit") model = AutoModelForImageClassification.from_pretrained("dewanakl/batik-vit") - Notebooks
- Google Colab
- Kaggle
hello word
Test Loss: 0.3272, Test Accuracy: 91.85%
https://drive.google.com/drive/folders/1vHZK2SAhO3SSklksp5Zy5uDbxmx-PHgK?usp=sharing
source: https://www.kaggle.com/datasets/alfanme/indonesian-batik-motifs-corak-app
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Model tree for dewanakl/batik-vit
Base model
microsoft/beit-base-patch16-224-pt22k-ft22k