Instructions to use ankitcodes/clear-document-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ankitcodes/clear-document-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="ankitcodes/clear-document-detection")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("ankitcodes/clear-document-detection") model = AutoModelForObjectDetection.from_pretrained("ankitcodes/clear-document-detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac25196498807c1f69d93f31b5723b4bd437293f6c11875c83cd71808581b7d3
- Size of remote file:
- 166 MB
- SHA256:
- 62f95dc8833c4f1dbbef26f7c530eb78d0e0d6f7c6a6664c0347fd2d218c6ad3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.