Instructions to use ericvo/scribbl-scan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ericvo/scribbl-scan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ericvo/scribbl-scan") 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("ericvo/scribbl-scan") model = AutoModelForImageClassification.from_pretrained("ericvo/scribbl-scan") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f6fec84c14f7cc5343668283ddd604a4d873f684e3750fe09ea07f8042514426
- Size of remote file:
- 343 MB
- SHA256:
- 3b5cfe2c1d39549fd9ad6c3c13b2f320ea6107f5771aace71f4f23ebf70747a6
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