Instructions to use kmewhort/beit-sketch-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kmewhort/beit-sketch-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kmewhort/beit-sketch-classifier") 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("kmewhort/beit-sketch-classifier") model = AutoModelForImageClassification.from_pretrained("kmewhort/beit-sketch-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 67bb53a4509ec4599263d6dc00fb6bf3d7de988ff11fb3cc471b0f33f81f4eb4
- Size of remote file:
- 348 MB
- SHA256:
- aecc427081cff0ff8e4e6478d99793bba56cf708c50c6662ded1b1d85e70259f
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