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:
- 25f54addc00e468c0ba80d67f4d482be63844943bdba91adb9706d7c63879ad8
- Size of remote file:
- 687 MB
- SHA256:
- d82abf7a2d71346cb612147f70e5ce2a52077c8b25ce2fd916a03f850465e346
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