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:
- 67a0aba824ac0d2eb696e71e09c96ef0d85387528199eae046e9817647fb58a0
- Size of remote file:
- 627 Bytes
- SHA256:
- 855c89b7f32eb731e9b96739f0342e3107e09b1ea38d6288849b304854c6b06a
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