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:
- 60197b7420b528f0c897155073ca5dc6092a28abe5866a24f9933352c39e0685
- Size of remote file:
- 3.52 kB
- SHA256:
- fff4ed1153097d62df0996406ba0cfda8f4340c1317b93f6c7c6f808a7fbcf48
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